Deck 12: Analysis of Variance

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Question
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-A consumer magazine wants to compare the lifetimes of ballpoint pens of three different types. The magazine takes a random sample of pens of each type in the following table.
 brandA brand B brand C 260181238218240257184162241219218213\begin{array}{lll}\text { brandA }&\text {brand B }&\text {brand C }\\\hline260 & 181 & 238 \\218 & 240 & 257 \\184 & 162 & 241 \\219 & 218 & 213\end{array}
Do the data indicate that there is a difference in mean lifetime for the three brands of ballpoint pens? Use  Use α=0.0\text { Use } \alpha = 0.0
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Question
Provide an appropriate response.

-Describe the null and alternative hypotheses for one-way ANOVA. Give an example.
Question
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-The data below represent the weight losses for people on three different exercise programs.
 Exercise A Exercise BExercise C 2.55.84.38.84.96.27.31.15.89.87.88.15.11.27.9\begin{array}{lll}\text { Exercise A}&\text { Exercise B}& \text {Exercise C }\\\hline2.5 & 5.8 & 4.3 \\8.8 & 4.9 & 6.2 \\7.3 & 1.1 & 5.8 \\9.8 & 7.8 & 8.1 \\5.1 & 1.2 & 7.9\end{array}
At the 1% significance level, does it appear that a difference exists in the true mean weight loss produced by the three exercise programs?
Question
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-At the 0.025 significance level, test the claim that the four brands have the same mean if the following sample results have been obtained.  brandA brand B brand C brand D 15202115251722152122201423231923221822202828\begin{array}{llll}\text { brandA }&\text {brand B }&\text {brand C }&\text {brand D }\\\hline15 & 20 & 21 & 15 \\25 & 17 & 22 & 15 \\21 & 22 & 20 & 14 \\23 & 23 & 19 & 23 \\22 & & 18 & 22 \\20 & & & 28\\&&&28\end{array}
Question
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  p  Factor 33010.001.60.264 Error 8506.25 Total 1180\begin{array} { l r c c c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Factor } & 3 & 30 & 10.00 & 1.6 & 0.264 \\\text { Error } & 8 & 50 & 6.25 & & \\\text { Total } & 11 & 80 & & &\end{array} Identify the value of the test statistic.

A)30
B)10.00
C)0.264
D)1.6
Question
Provide an appropriate response.
Provide an appropriate response.  <div style=padding-top: 35px>
Question
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  P  Factor 313.5004.5005.170.011 Error 1613.9250.870 Total 1927.425\begin{array} { l r c c c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { P } \\\text { Factor } & 3 & 13.500 & 4.500 & 5.17 & 0.011 \\\text { Error } & 16 & 13.925 & 0.870 & & \\\text { Total } & 19 & 27.425 & & &\end{array} Identify the value of the test statistic.

A)13.500
B)0.011
C)5.17
D)4.500
Question
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-Given the sample data below, test the claim that the populations have the same mean. Use a significance level of 0.05.  Brand A  Brand B  Brand C  Brand D n=16n=16n=16n=16xˉ=2.09xˉ=3.48xˉ=1.86xˉ=2.84s=0.37 s=0.61 s=0.45 s=0.53\begin{array} { l } \text { Brand A }& \text { Brand B } &\text { Brand C } & \text { Brand D } \\{ n = 16 } &{ n = 16 } & { n = 16 } &{ n = 16 } \\\bar { x } = 2.09& \bar { x } = 3.48 & \bar { x } = 1.86 & \bar { x } = 2.84 \\s = 0.37 & \mathrm {~s} = 0.61& \mathrm {~s} = 0.45 & \mathrm {~s} = 0.53 \\\end{array}
Question
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  p  Factor 313.5004.5005.170.011 Error 1613.9250.870 Total 1927.425\begin{array} { l r c c c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Factor } & 3 & 13.500 & 4.500 & 5.17 & 0.011 \\\text { Error } & 16 & 13.925 & 0.870 & & \\\text { Total } & 19 & 27.425 & & &\end{array} What can you conclude about the equality of the population means?

A)Accept the null hypothesis since the p-value is less than the significance level.
B)Reject the null hypothesis since the p-value is greater than the significance level.
C)Reject the null hypothesis since the p-value is less than the significance level.
D)Accept the null hypothesis since the p-value is greater than the significance level.
Question
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-Given the sample data below, test the claim that the populations have the same mean. Use a significance level of 0.05.  Brand A Brand B Brand Cn=10n=10n=10x=32.6x=31.7x=27.4 s2=4.51 s2=4.22 s2=4.69\begin{array}{ccc}\text { Brand } \mathrm{A} &\text { Brand } \mathrm{B} &\text { Brand } \mathrm{C}\\\hline\mathrm{n}=10 & \mathrm{n}=10 & \mathrm{n}=10 \\\overline{\mathrm{x}}=32.6 & \overline{\mathrm{x}}=31.7 & \overline{\mathrm{x}}=27.4 \\\mathrm{~s}^{2}=4.51 & \mathrm{~s}^{2}=4.22 & \mathrm{~s}^{2}=4.69\end{array}
Question
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  p  Factor 313.5004.5005.170.011 Error 1613.9250.870 Total 1927.425\begin{array} { l r c l c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Factor } & 3 & 13.500 & 4.500 & 5.17 & 0.011 \\\text { Error } & 16 & 13.925 & 0.870 & & \\\text { Total } & 19 & 27.425 & & &\end{array} Identify the p-value.

A)0.011
B)4.500
C)5.17
D)0.870
Question
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  p  Factor 33010.001.60.264 Error 8506.25 Total 1180\begin{array} { l r c c c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Factor } & 3 & 30 & 10.00 & 1.6 & 0.264 \\\text { Error } & 8 & 50 & 6.25 & & \\\text { Total } & 11 & 80 & & &\end{array} Find the critical value.

A)1.6
B)8.85
C)4.07
D)7.59
Question
Provide an appropriate response.

-  The test statistic for one-way ANOVA is F= variance between samples  variance within samples . Describe variance within samples and \text { The test statistic for one-way ANOVA is } F = \frac { \text { variance between samples } } { \text { variance within samples } } \text {. Describe variance within samples and } variance between samples. What relationship between variance within samples and variance between samples would result in the conclusion that the value of F is significant?
Question
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-Random samples of four different models of cars were selected and the gas mileage of each car was measured. The results are shown below.  Model A Model B Model C Model D 23283025252628262429322526302728\begin{array}{llll}\text { Model A }&\text {Model B }&\text {Model C }&\text {Model D }\\\hline23 & 28 & 30 & 25 \\25 & 26 & 28 & 26 \\24 & 29 & 32 & 25 \\26 & 30 & 27 & 28\end{array} Test the claim that the four different models have the same population mean. Use a significance level of 0.05.
Question
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-At the 0.025 significance level, test the claim that the three brands have the same mean if the following sample results have been obtained.  brand A brand B brand C 322722342425373332333022362139\begin{array}{lll}\text { brand A }&\text {brand B }&\text {brand C }&\\\hline32 & 27 & 22 \\34 & 24 & 25 \\37 & 33 & 32 \\33 & 30 & 22 \\36 & & 21 \\39 & &\end{array}
Question
Provide an appropriate response.

-When using statistical software packages, the critical value is typically not given. What method is used to determine whether you reject or fail to reject the null hypothesis?
Question
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  p  Factor 313.5004.5005.170.011 Error 1613.9250.870 Total 1927.425\begin{array} { l r c c c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Factor } & 3 & 13.500 & 4.500 & 5.17 & 0.011 \\\text { Error } & 16 & 13.925 & 0.870 & & \\\text { Total } & 19 & 27.425 & & &\end{array} Find the critical value.

A)3.24
B)8.70
C)5.42
D)3.06
Question
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  p  Factor 33010.001.60.264 Error 8506.25 Total 1180\begin{array} { l r c c c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Factor } & 3 & 30 & 10.00 & 1.6 & 0.264 \\\text { Error } & 8 & 50 & 6.25 & & \\\text { Total } & 11 & 80 & & &\end{array} Identify the p-value.

A)0.264
B)10.00
C)6.25
D)1.6
Question
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  p  Factor 33010.001.60.264 Error 8506.25 Total 1180\begin{array} { l r c c c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Factor } & 3 & 30 & 10.00 & 1.6 & 0.264 \\\text { Error } & 8 & 50 & 6.25 & & \\\text { Total } & 11 & 80 & & &\end{array} What can you conclude about the equality of the population means?

A)Reject the null hypothesis since the p-value is less than the significance level.
B)Reject the null hypothesis since the p-value is greater than the significance level.
C)Accept the null hypothesis since the p-value is greater than the significance level.
D)Accept the null hypothesis since the p-value is less than the significance level.
Question
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-At the 0.025 significance level, test the claim that the four brands have the same mean if the following sample results have been obtained.  brandA brand B brand C brand D 1718212220182425212325272225262921262935293637\begin{array}{llll}\text { brandA }&\text {brand B }&\text {brand C }&\text {brand D }\\\hline17 & 18 & 21 & 22 \\20 & 18 & 24 & 25 \\21 & 23 & 25 & 27 \\22 & 25 & 26 & 29 \\21 & 26 & 29 & 35 \\& & 29 & 36 \\& & & 37\end{array}
Question
Provide an appropriate response.

-Fill in the missing entries in the following partially completed one-way ANOVA table.  Source  df  SS  MS=SS/df  F-statistic  Treatment 311.16 Error 13.720.686 Total \begin{array}{|l|r|r|l|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 3 & & & 11.16 \\\hline \text { Error } & & 13.72 & 0.686 & \\\hline \text { Total } & & & & \\\hline\end{array}

A)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 30.1840.06111.16 Error 2013.720.686 Total 2313.90\begin{array}{|l|r|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 3 & 0.184 & 0.061 & 11.16 \\\hline \text { Error } & 20 & 13.72 & 0.686 & \\\hline \text { Total } & 23 & 13.90 & & \\\hline\end{array}
B)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 322.977.6611.16 Error 2013.720.686 Total 2336.69\begin{array}{|l|r|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 3 & 22.97 & 7.66 & 11.16 \\\hline \text { Error } & 20 & 13.72 & 0.686 & \\\hline \text { Total } & 23 & 36.69 & & \\\hline\end{array}
C)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 348.8016.2711.16 Error 2013.720.686 Total 2362.52\begin{array}{|l|c|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 3 & 48.80 & 16.27 & 11.16 \\\hline \text { Error } & 20 & 13.72 & 0.686 & \\\hline \text { Total } & 23 & 62.52 & & \\\hline\end{array}
D)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 32.557.6611.16 Error 2013.720.686 Total 2316.27\begin{array}{|l|c|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 3 & 2.55 & 7.66 & 11.16 \\\hline \text { Error } & 20 & 13.72 & 0.686 & \\\hline \text { Total } & 23 & 16.27 & & \\\hline\end{array}
Question
At the same time each day, a researcher records the temperature in each of three greenhouses. The table shows the temperatures in degrees Fahrenheit recorded for one week.  Greenhouse #1  Greenhouse #2  Greenhouse #3 737167726963737262667261686560717362727159\begin{array} { c | c | c } \text { Greenhouse \#1 } & \text { Greenhouse \#2 } & \text { Greenhouse \#3 } \\\hline 73 & 71 & 67 \\72 & 69 & 63 \\73 & 72 & 62 \\66 & 72 & 61 \\68 & 65 & 60 \\71 & 73 & 62 \\72 & 71 & 59\end{array} i)Use a 0.05 significance level to test the claim that the average temperature is the same in each greenhouse. ii)How are the analysis of variance results affected if the same constant is added to every one of the original sample values?
Question
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 31,34,3229,23,2221,20,24 Machine  II 19,26,2235,33,3025,19,23 III 21,18,2620,23,2436,37,31 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 21.19.59 EMPLOYEE 25.852.93 INTERACTION 4710.81177.70 ERROR 18160.008.89 TOTAL 26877.85\begin{array}{l}\begin{array} { r r c c c } &&& { \text { Employee } } \\& & \text { A } & \text { B } & \text { C } \\& \text { I } & 31,34,32 & 29,23,22 & 21,20,24 \\\text { Machine } & \text { II } & 19,26,22 & 35,33,30 & 25,19,23 \\& \text { III } & 21,18,26 & 20,23,24 & 36,37,31\end{array}\\\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } & { \text { SS } } & \text { MS } \\\text { MACHINE } & 2 & 1.19 & .59 \\\text { EMPLOYEE } & 2 & 5.85 & 2.93 \\\text { INTERACTION } & 4 & 710.81 & 177.70 \\\text { ERROR } & 18 & 160.00 & 8.89 \\\text { TOTAL } & 26 & 877.85 &\end{array}\end{array} Assume that the number of items produced is not affected by an interaction between employee and machine. Using a 0.05 significance level, test the claim that the choice of employee has no effect on the number of items produced.
Question
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 16,18,1915,17,2014,18,16 Machine  II 20,27,2925,28,2729,28,26 III 15,18,1716,16,1913,17,16 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 2588.74294.37 EMPLOYEE 22.071.04 INTERACTION 415.483.87 ERROR 1898.675.48 TOTAL 26704.96\begin{array}{l}\begin{array} { r r c c c } & &&{ \text { Employee } } \\& & \text { A } & \text { B } & \text { C } \\& \text { I } & 16,18,19 & 15,17,20 & 14,18,16 \\\text { Machine } & \text { II } & 20,27,29 & 25,28,27 & 29,28,26 \\& \text { III } & 15,18,17 & 16,16,19 & 13,17,16\end{array}\\\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } &{ \text { SS } } &{ \text { MS } } \\\text { MACHINE } & 2 & 588.74 & 294.37 \\\text { EMPLOYEE } & 2 & 2.07 & 1.04 \\\text { INTERACTION } & 4 & 15.48 & 3.87 \\\text { ERROR } & 18 & 98.67 & 5.48 \\\text { TOTAL } & 26 & 704.96 &\end{array}\end{array} Assume that the number of items produced is not affected by an interaction between employee and machine. Using a 0.05 significance level, test the claim that the choice of employee has no effect on the number of items produced.
Question
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 31,34,3229,23,2221,20,24 Machine  II 19,26,2235,33,3025,19,23 III 21,18,2620,23,2436,37,31 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 21.19.59 EMPLOYEE 25.852.93 INTERACTION 4710.81177.70 ERROR 18160.008.89 TOTAL 26877.85\begin{array}{l}\begin{array} { r r c c c } && { \text { Employee } } \\&& { \text { A } } & \text { B } & \text { C } \\& \text { I } & 31,34,32 & 29,23,22 & 21,20,24 \\\text { Machine } & \text { II } & 19,26,22 & 35,33,30 & 25,19,23 \\& \text { III } & 21,18,26 & 20,23,24 & 36,37,31\end{array}\\\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } & { \text { SS } } & \text { MS } \\\text { MACHINE } & 2 & 1.19 & .59 \\\text { EMPLOYEE } & 2 & 5.85 & 2.93 \\\text { INTERACTION } & 4 & 710.81 & 177.70 \\\text { ERROR } & 18 & 160.00 & 8.89 \\\text { TOTAL } & 26 & 877.85 &\end{array}\end{array} Using a 0.05 significance level, test the claim that the interaction between employee and machine has no effect on the number of items produced.
Question
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 23,27,2930,27,2518,20,22 Machine II 25,26,2424,29,2619,16,14 III 28,25,2625,27,2315,11,17 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 234.6717.33 EMPLOYEE 2504.67252.33 INTERACTION 426.676.67 ERROR 1898.005.44 TOTAL 26664.00\begin{array}{l}\begin{array}{rccc} &&\text { Employee }\\& \text { A } & \text { B } & \text { C } \\\text { I } & 23,27,29 & 30,27,25 & 18,20,22 \\\text { Machine II } & 25,26,24 & 24,29,26 & 19,16,14 \\\text { III } & 28,25,26 & 25,27,23 & 15,11,17\end{array}\\\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } & { \text { SS } } & { \text { MS } } \\\text { MACHINE } & 2 & 34.67 & 17.33 \\\text { EMPLOYEE } & 2 & 504.67 & 252.33 \\\text { INTERACTION } & 4 & 26.67 & 6.67 \\\text { ERROR } & 18 & 98.00 & 5.44 \\\text { TOTAL } & 26 & 664.00 &\end{array}\end{array} Assume that the number of items produced is not affected by an interaction between employee and machine. Using a 0.05 significance level, test the claim that the choice of employee has no effect on the number of items produced.
Question
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.
 Employee  A  B  C  Machine  II 16,18,1915,17,2014,18,16 II 20,27,2925,28,2729,28,26 III 15,18,1716,16,1913,17,16\begin{array}{rrccc} &&&{\text { Employee }} \\& & \text { A } & \text { B } & \text { C } \\\text { Machine } & \text { II } & 16,18,19 & 15,17,20 & 14,18,16 \\& \text { II } & 20,27,29 & 25,28,27 & 29,28,26 \\& \text { III } & 15,18,17 & 16,16,19 & 13,17,16\end{array}

 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 2588.74294.37 EMPLOYEE 22.071.04 INTERACTION 415.483.87 ERROR 1898.675.48 TOTAL 26704.96\begin{array}{l}\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array}{lrrr}\text { SOURCE } & \text { DF } &{\text { SS }} & {\text { MS }} \\\text { MACHINE } & 2 & 588.74 & 294.37 \\\text { EMPLOYEE } & 2 & 2.07 & 1.04 \\\text { INTERACTION } & 4 & 15.48 & 3.87 \\\text { ERROR } & 18 & 98.67 & 5.48 \\\text { TOTAL } & 26 & 704.96 &\end{array}\end{array}
Using a 0.05 significance level, test the claim that the interaction between employee and machine has no effect on the number of items produced.
Question
Six independent samples of 100 values each are randomly drawn from populations that are normally distributed with equal variances. You wish to test the claim that μ1=μ2=μ3=μ4=μ5=μ6\mu _ { 1 } = \mu _ { 2 } = \mu _ { 3 } = \mu _ { 4 } = \mu _ { 5 } = \mu _ { 6 } .
If you test the individual claims μ1=μ2,μ1=μ3,μ1=μ4,,μ5=μ6\mu _ { 1 } = \mu _ { 2 } , \mu _ { 1 } = \mu _ { 3 } , \mu _ { 1 } = \mu _ { 4 } , \ldots , \mu _ { 5 } = \mu _ { 6 } , how many ways can you pair off the means?
i) Assume that the tests are independent and that for each test of equality between two means, there is a 0.900.90 probability of not making a type I error. If all possible pairs of means are tested for equality, what is the probabi making no type I errors?
ii) If you use analysis of variance to test the claim that μ1=μ2=μ3=μ4=μ5=μ6\mu _ { 1 } = \mu _ { 2 } = \mu _ { 3 } = \mu _ { 4 } = \mu _ { 5 } = \mu _ { 6 } at the 0.100.10 level of significan what is the probability of not making a type I error?
Question
Four independent samples of 100 values each are randomly drawn from populations that are normally distributed with equal variances. You wish to test the claim that μ1=μ2=μ3=μ4\mu _ { 1 } = \mu _ { 2 } = \mu _ { 3 } = \mu _ { 4 } .
If you test the individual claims μ1=μ2,μ1=μ3,μ1=μ4,,μ3=μ4\mu _ { 1 } = \mu _ { 2 } , \mu _ { 1 } = \mu _ { 3 } , \mu _ { 1 } = \mu _ { 4 } , \ldots , \mu _ { 3 } = \mu _ { 4 } , how many ways can you pair off the means?
ii) Assume that the tests are independent and that for each test of equality between two means, there is a 0.990.99 probability of not making a type I error. If all possible pairs of means are tested for equality, what is the probabi making no type I errors?
iii) If you use analysis of variance to test the claim that μ1=μ2=μ3=μ4\mu _ { 1 } = \mu _ { 2 } = \mu _ { 3 } = \mu _ { 4 } at the 0.010.01 level of significance, what is the probability of not making a type I error?
Question
The following table entries are the times in seconds for three different drivers racing on four different tracks. Assuming no effect from the interaction between driver and track, test the claim that the three drivers have the same mean time. Use a 0.05 significance level.  Track 1  Track 2  Track 3  Track 4  Driver 1 72706871 Driver 2 74716672 Driver 3 76696470\begin{array}{c|cccc} & \text { Track 1 } & \text { Track 2 } & \text { Track 3 } & \text { Track 4 } \\\hline \text { Driver 1 } & 72 & 70 & 68 & 71 \\\text { Driver 2 } & 74 & 71 & 66 & 72 \\\text { Driver 3 } & 76 & 69 & 64 & 70\end{array}
 Source  DF  SS  MS  F  p  Driver 2210.330.729 Track 398.2532.7510.920.00763 Error 6183 Total 11118.25\begin{array} { l r c l r c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Driver } & 2 & 2 & 1 & 0.33 & 0.729 \\\text { Track } & 3 & 98.25 & 32.75 & 10.92 & 0.00763 \\\text { Error } & 6 & 18 & 3 & & \\\text { Total } & 11 & 118.25 & & &\end{array}
Question
At the same time each day, a researcher records the temperature in each of three greenhouses. The table shows the temperatures in degrees Fahrenheit recorded for one week.  Greenhouse #1  Greenhouse #2  Greenhouse # 737167726963737262667261686560717362727159\begin{array} { c | c | c } \text { Greenhouse \#1 } & \text { Greenhouse \#2 } & \text { Greenhouse \# } \\\hline 73 & 71 & 67 \\72 & 69 & 63 \\73 & 72 & 62 \\66 & 72 & 61 \\68 & 65 & 60 \\71 & 73 & 62 \\72 & 71 & 59\end{array} i)Use a 0.05 significance level to test the claim that the average temperature is the same in each greenhouse. ii)How are the analysis of variance results affected if 8° is added to each temperature listed for greenhouse #3?
Question
Provide an appropriate response.

-Fill in the missing entries in the following partially completed one-way ANOVA table.  Source  df  SS  MS=SS/df  F-statistic  Treatment 25.2 Error 243.5 Total 28\begin{array}{|l|c|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & & 25.2 & & \\\hline \text { Error } & 24 & & 3.5 & \\\hline \text { Total } & 28 & & & \\\hline\end{array}

A)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 425.26.301.80 Error 2484.03.5 Total 2825.35\begin{array}{|l|c|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 4 & 25.2 & 6.30 & 1.80 \\\hline \text { Error } & 24 & 84.0 & 3.5 & \\\hline \text { Total } & 28 & 25.35 & & \\\hline\end{array}
B)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 425.26.300.56 Error 2484.03.5 Total 28109.2\begin{array}{|l|c|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 4 & 25.2 & 6.30 & 0.56 \\\hline \text { Error } & 24 & 84.0 & 3.5 & \\\hline \text { Total } & 28 & 109.2 & & \\\hline\end{array}
C)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 425.26.301.80 Error 2484.03.5 Total 28109.2\begin{array}{|l|c|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 4 & 25.2 & 6.30 & 1.80 \\\hline \text { Error } & 24 & 84.0 & 3.5 & \\\hline \text { Total } & 28 & 109.2 & & \\\hline\end{array}
D)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 5225.20.48374.40 Error 2484.03.5 Total 28109.2\begin{array}{|l|c|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 52 & 25.2 & 0.48 & 374.40 \\\hline \text { Error } & 24 & 84.0 & 3.5 & \\\hline \text { Total } & 28 & 109.2 & & \\\hline\end{array}
Question
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 23,27,2930,27,2518,20,22 Machine  II 25,26,2424,29,2619,16,14 III 28,25,2625,27,2315,11,17 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 234.6717.33 EMPLOYEE 2504.67252.33 INTERACTION 426.676.67 ERROR 1898.005.44 TOTAL 26664.00\begin{array}{l}\begin{array} { r r r c c } &&&{ \text { Employee } } \\& & \text { A } & \text { B } & \text { C } \\& \text { I } & 23,27,29 & 30,27,25 & 18,20,22 \\\text { Machine } & \text { II } & 25,26,24 & 24,29,26 & 19,16,14 \\& \text { III } & 28,25,26 & 25,27,23 & 15,11,17\end{array}\\\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } & { \text { SS } } & { \text { MS } } \\\text { MACHINE } & 2 & 34.67 & 17.33 \\\text { EMPLOYEE } & 2 & 504.67 & 252.33 \\\text { INTERACTION } & 4 & 26.67 & 6.67 \\\text { ERROR } & 18 & 98.00 & 5.44 \\\text { TOTAL } & 26 & 664.00 &\end{array}\end{array} Using a 0.05 significance level, test the claim that the interaction between employee and machine has no effect on the number of items produced.
Question
The following table entries are test scores for males and females at different times of day. Assuming no effect from the interaction between gender and test time, test the claim that males and females perform the same on the test. Use a 0.05 significance level. 6 a.m. - 9 a.m. 9 a.m. 12 p.m. 12 p.m. - 3 p.m. 3p.m.6 p.m.  Male 87899285 Female 72849489 Source  DF  SS  MS  F  p  Gender 124.524.50.66520.4745 Time 3183611.65610.3444 Error 3110.536.83 Total 7318\begin{array}{l}\begin{array} { l | c c c c } & 6 \text { a.m. - } 9 \text { a.m. } &9 \text { a.m. } - 12 \text { p.m. } &12 \text { p.m. - 3 p.m. } &3 p.m. - 6 \text { p.m. } \\\hline \text { Male } & 87 & 89 & 92 & 85 \\\text { Female } & 72 & 84 & 94 & 89\end{array}\\\begin{array} { l c c l c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Gender } & 1 & 24.5 & 24.5 & 0.6652 & 0.4745 \\\text { Time } & 3 & 183 & 61 & 1.6561 & 0.3444 \\\text { Error } & 3 & 110.5 & 36.83 & & \\\text { Total } & 7 & 318 & & &\end{array}\end{array}
Question
The following table entries are the times in seconds for three different drivers racing on four different tracks. Assuming no effect from the interaction between driver and track, test the claim that the track has no effect on the time. Use a 0.05 significance level.  Track 1  Track 2  Track 3  Track 4  Driver 1 72706871 Driver 2 74716672 Driver 3 76696470 Source  DF  SS  MS  F  p  Driver 2210.330.729 Track 398.2532.7510.920.00763 Error 6183 Total 11118.25\begin{array}{l}\begin{array} { c | c c c c } & \text { Track 1 } & \text { Track 2 } & \text { Track 3 } & \text { Track 4 } \\\hline \text { Driver 1 } & 72 & 70 & 68 & 71 \\\text { Driver 2 } & 74 & 71 & 66 & 72 \\\text { Driver 3 } & 76 & 69 & 64 & 70\end{array}\\\\\begin{array} { l r c l r l } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Driver } & 2 & 2 & 1 & 0.33 & 0.729 \\\text { Track } & 3 & 98.25 & 32.75 & 10.92 & 0.00763 \\\text { Error } & 6 & 18 & 3 & & \\\text { Total } & 11 & 118.25 & & &\end{array}\end{array}
Question
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 31,34,3229,23,2221,20,24 Machine  II 19,26,2235,33,3025,19,23 III 21,18,2620,23,2436,37,31 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 21.19.59 EMPLOYEE 25.852.93 INTERACTION 4710.81177.70 ERROR 18160.008.89 TOTAL 26877.85\begin{array}{l}\begin{array} { r r c c c } &&&{ \text { Employee } } \\& & \text { A } & \text { B } & \text { C } \\& \text { I } & 31,34,32 & 29,23,22 & 21,20,24 \\\text { Machine } & \text { II } & 19,26,22 & 35,33,30 & 25,19,23 \\& \text { III } & 21,18,26 & 20,23,24 & 36,37,31\end{array}\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } & { \text { SS } } & \text { MS } \\\text { MACHINE } & 2 & 1.19 & .59 \\\text { EMPLOYEE } & 2 & 5.85 & 2.93 \\\text { INTERACTION } & 4 & 710.81 & 177.70 \\\text { ERROR } & 18 & 160.00 & 8.89 \\\text { TOTAL } & 26 & 877.85 &\end{array}\end{array} Assume that the number of items produced is not affected by an interaction between employee and machine. Using a 0.05 significance level, test the claim that the machine has no effect on the number of items produced.
Question
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 16,18,1915,17,2014,18,16 Machine  II 20,27,2925,28,2729,28,26 III 15,18,1716,16,1913,17,16 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 2588.74294.37 EMPLOYEE 22.071.04 INTERACTION 415.483.87 ERROR 1898.675.48 TOTAL 26704.96\begin{array}{l}\begin{array} { r r c c c } & && { \text { Employee } } \\& & \text { A } & \text { B } & \text { C } \\& \text { I } & 16,18,19 & 15,17,20 & 14,18,16 \\\text { Machine } & \text { II } & 20,27,29 & 25,28,27 & 29,28,26 \\& \text { III } & 15,18,17 & 16,16,19 & 13,17,16\end{array}\\\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } & { \text { SS } } & { \text { MS } } \\\text { MACHINE } & 2 & 588.74 & 294.37 \\\text { EMPLOYEE } & 2 & 2.07 & 1.04 \\\text { INTERACTION } & 4 & 15.48 & 3.87 \\\text { ERROR } & 18 & 98.67 & 5.48 \\\text { TOTAL } & 26 & 704.96 &\end{array}\end{array} Assume that the number of items produced is not affected by an interaction between employee and machine. Using a 0.05 significance level, test the claim that the machine has no effect on the number of items produced.
Question
Use the data given below to verify that the t test for independent samples and the ANOVA method are equivalent. AB101929181127193015181621\begin{array} { c | c } \mathrm { A } & \mathrm { B } \\\hline 10 & 19 \\29 & 18 \\11 & 27 \\19 & 30 \\15 & 18 \\16 & 21\end{array} i)Use a t test with a 0.05 significance level to test the claim that the two samples come from populations with the same means. ii)Use the ANOVA method with a 0.05 significance level to test the same claim. iii)Verify that the squares of the t test statistic and the critical value are equal to the F test statistic and critical value.
Question
Use the data given below to verify that the t test for independent samples and the ANOVA method are equivalent. AB85748172736591836459\begin{array} { c | c } \mathrm { A } & \mathrm { B } \\\hline 85 & 74 \\81 & 72 \\73 & 65 \\91 & 83 \\64 & 59\end{array} i)Use a t test with a 0.05 significance level to test the claim that the two samples come from populations with the same means. ii)Use the ANOVA method with a 0.05 significance level to test the same claim. iii)Verify that the squares of the t test statistic and the critical value are equal to the F test statistic and critical value.
Question
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 23,27,2930,27,2518,20,22 Machine  II 25,26,2424,29,2619,16,14 III 28,25,2625,27,2315,11,17 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 234.6717.33 EMPLOYEE 2504.67252.33 INTERACTION 426.676.67 ERROR 1898.005.44 TOTAL 26664.00\begin{array}{l}\begin{array} { l r c c c } & &&{ \text { Employee } } \\&& { \text { A } } & \text { B } & \text { C } \\& \text { I } & 23,27,29 & 30,27,25 & 18,20,22 \\\text { Machine } & \text { II } & 25,26,24 & 24,29,26 & 19,16,14 \\& \text { III } & 28,25,26 & 25,27,23 & 15,11,17\end{array}\\\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } & { \text { SS } } & \text { MS } \\\text { MACHINE } & 2 & 34.67 & 17.33 \\\text { EMPLOYEE } & 2 & 504.67 & 252.33 \\\text { INTERACTION } & 4 & 26.67 & 6.67 \\\text { ERROR } & 18 & 98.00 & 5.44 \\\text { TOTAL } & 26 & 664.00 &\end{array}\end{array} Assume that the number of items produced is not affected by an interaction between employee and machine. Using a 0.05 significance level, test the claim that the machine has no effect on the number of items produced.
Question
The following data contains task completion times, in minutes, categorized according to the gender of the machine operator and the machine used.
 malefemale Machine 1 15,1716,17Machine 214,1315,13 Machine 316,1817,19\begin{array} { l } & \text { male}& \text {female }\\ \text {Machine 1 }&15,17&16,17\\ \text {Machine 2}&14,13&15,13\\ \text { Machine 3}&16,18&17,19\\\end{array}
Assume that two-way ANOVA is used to analyze the data. How are the ANOVA results affected if the first sample value in the first cell is changed to 30 minutes?
Question
The following data shows annual income, in thousands of dollars, categorized according to the two factors of gender and level of education. Assume that incomes are not affected by an interaction between gender and level of education, and test the null hypothesis that gender has no effect on income. Use a 0.05 significance level.  Female  Male  High school 23,27,24,2625,26,22,24 College 28,36,31,3335,32,39,28 Advanced degree 41,38,43,4935,50,47,44\begin{array} { l c c } & \text { Female } & \text { Male } \\\text { High school } & 23,27,24,26 & 25,26,22,24 \\\text { College } & 28,36,31,33 & 35,32,39,28 \\\text { Advanced degree } & 41,38,43,49 & 35,50,47,44\end{array}
Question
The following data shows the yield, in bushels per acre, categorized according to three varieties of corn and three different soil conditions. Assume that yields are not affected by an interaction between variety and soil conditions, and test the null hypothesis that soil conditions have no effect on yield. Use a 0.05 significance level.  Plot 1  Plot 2  Plot 3  Variety 1 156,167,162,160,145,151170,162169,168148,155 Variety 2 172,176,179,186,161,162,166,179160,176165,170 Variety 3 175,157,178,170,169,165,179,178172,174170,169\begin{array}{cccc} & \text { Plot 1 } & \text { Plot 2 } & \text { Plot 3 } \\\text { Variety 1 } & 156,167, & 162,160, & 145,151 \text {, } \\& 170,162 & 169,168 & 148,155 \\\text { Variety 2 } & 172,176, & 179,186, & 161,162, \\& 166,179 & 160,176 & 165,170 \\\text { Variety 3 } & 175,157, & 178,170, & 169,165, \\& 179,178 & 172,174 & 170,169\end{array}
Question
The following data contains task completion times, in minutes, categorized according to the gender of the machine operator and the machine used.
 malefemale Machine 1 15,1716,17Machine 214,1315,13 Machine 316,1817,19\begin{array} { l } & \text { male}& \text {female }\\ \text {Machine 1 }&15,17&16,17\\ \text {Machine 2}&14,13&15,13\\ \text { Machine 3}&16,18&17,19\\\end{array}
The ANOVA results lead us to conclude that the completion times are not affected by an interaction between machine and gender, and the times are not affected by gender, but they are affected by the machine. Change the table entries so that there is no effect from the interaction between machine and gender, but there is an effect from the gender of the operator.
Question
The following data contains task completion times, in minutes, categorized according to the gender of the machine operator and the machine used.
 Male  Female  Machine 1 15,1716,17 Machine 2 14,1315,13 Machine 3 16,1817,19\begin{array}{lrl} & \text { Male } & \text { Female } \\\text { Machine 1 } & 15,17 & 16,17 \\\text { Machine 2 } & 14,13 & 15,13 \\\text { Machine 3 } & 16,18 & 17,19\end{array}
Assume that two-way ANOVA is used to analyze the data. How are the ANOVA results affected if the times are all doubled?
Question
The following data contains task completion times, in minutes, categorized according to the gender of the machine operator and the machine used.
 Male  Female  Machine 1 15,1716,17 Machine 2 14,1315,13 Machine 3 16,1817,19\begin{array}{lrl} & \text { Male } & \text { Female } \\\text { Machine 1 } & 15,17 & 16,17 \\\text { Machine 2 } & 14,13 & 15,13 \\\text { Machine 3 } & 16,18 & 17,19\end{array}
Assume that two-way ANOVA is used to analyze the data. How are the ANOVA results affected if 5 minutes is added to each completion time?
Question
The following data contains task completion times, in minutes, categorized according to the gender of the machine operator and the machine used.
 Male  Female  Machine 1 15,1716,17 Machine 2 14,1315,13 Machine 3 16,1817,19\begin{array}{lrl} & \text { Male } & \text { Female } \\\text { Machine 1 } & 15,17 & 16,17 \\\text { Machine 2 } & 14,13 & 15,13 \\\text { Machine 3 } & 16,18 & 17,19\end{array}
Assume that two-way ANOVA is used to analyze the data. How are the ANOVA results affected if the times are converted to hours?
Question
The following data shows the yield, in bushels per acre, categorized according to three varieties of corn and three different soil conditions. Assume that yields are not affected by an interaction between variety and soil conditions, and test the null hypothesis that variety has no effect on yield. Use a 0.05 significance level.
 Plot 1  Plot 2  Plot 3  Variety 1 156,167,162,160,145,151170,162169,168148,155 Variety 2 172,176,179,186,161,162166,179160,176165,170 Variety 3 175,157,178,170,169,165179,178172,174170,169\begin{array}{clcc} & \text { Plot 1 } & \text { Plot 2 } & \text { Plot 3 } \\\text { Variety 1 } & 156,167, & 162,160, & 145,151 \\& 170,162 & 169,168 & 148,155 \\\text { Variety 2 } & 172,176, & 179,186, & 161,162 \\& 166,179 & 160,176 & 165,170 \\\text { Variety 3 } & 175,157, & 178,170, & 169,165 \\& 179,178 & 172,174 & 170,169\end{array}
Question
The following data shows annual income, in thousands of dollars, categorized according to the two factors of gender and level of education. Assume that incomes are not affected by an interaction between gender and level of education, and test the null hypothesis that level of education has no effect on income. Use a 0.05 significance level.  Female  Male  High school 23,27,24,2625,26,22,24 College 28,36,31,3335,32,39,28 Advanced degree 41,38,43,4935,50,47,44\begin{array} { l c c } & \text { Female } & \text { Male } \\\text { High school } & 23,27,24,26 & 25,26,22,24 \\\text { College } & 28,36,31,33 & 35,32,39,28 \\\text { Advanced degree } & 41,38,43,49 & 35,50,47,44\end{array}
Question
The following table entries are test scores for males and females at different times of day. Assuming no effect from the interaction between gender and test time, test the claim that time of day does not affect test scores. Use a 0.05 significance level. 6 a.m. 9 a.m. 9 a.m. 12 p.m. 12 p.m. 3 p.m.3p.m.6 p.m.  Male 87899285 Female 72849489 Source  DF  SS  MS  F  p  Gender 124.524.50.66520.4745 Time 3183611.65610.3444 Error 3110.536.83 Total 7318\begin{array}{l}\begin{array} { l | c c c c } & 6 \text { a.m. } - 9 \text { a.m. } &9 \text { a.m. } - 12 \text { p.m. } &12 \text { p.m. } - 3 \text { p.m.}& 3 p.m. - 6 \text { p.m. } \\\hline \text { Male } & 87 & 89 & 92 & 85 \\\text { Female } & 72 & 84 & 94 & 89\end{array}\\\begin{array} { l c l l c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Gender } & 1 & 24.5 & 24.5 & 0.6652 & 0.4745 \\\text { Time } & 3 & 183 & 61 & 1.6561 & 0.3444 \\\text { Error } & 3 & 110.5 & 36.83 & & \\\text { Total } & 7 & 318 & & &\end{array}\end{array}
Question
The following Minitab display results from a study in which three different teachers taught calculus classes of five different sizes. The class average was recorded for each class. Assuming no effect from the interaction between teacher and class size, test the claim that class size has no effect on the class average. Use a 0.05 significance level.  Source  DF  SS  MS  F  p  Teacher 256.9328.471.0180.404 Class Size 4672.67168.176.0130.016 Error 8223.7327.97 Total 14953.33\begin{array} { l r r r c c } \text { Source } & \text { DF } & \text { SS } & { \text { MS } } & \text { F } & \text { p } \\\text { Teacher } & 2 & 56.93 & 28.47 & 1.018 & 0.404 \\\text { Class Size } & 4 & 672.67 & 168.17 & 6.013 & 0.016 \\\text { Error } & 8 & 223.73 & 27.97 & & \\\text { Total } & 14 & 953.33 & & &\end{array}
Question
The following data contains task completion times, in minutes, categorized according to the gender of the machine operator and the machine used.
 malefemale Machine 1 15,1716,17Machine 214,1315,13 Machine 316,1817,19\begin{array} { l } & \text { male}& \text {female }\\ \text {Machine 1 }&15,17&16,17\\ \text {Machine 2}&14,13&15,13\\ \text { Machine 3}&16,18&17,19\\\end{array}
The ANOVA results lead us to conclude that the completion times are not affected by an interaction between machine and gender, and the times are not affected by gender, but they are affected by the machine. Change the table entries so that there is an effect from the interaction between machine and gender.
Question
The following table shows the mileage for four different cars and three different brands of gas. Assuming no effect from the interaction between car and brand of gas, test the claim that the three brands of gas provide the same mean gas mileage. Use a 0.05 significance level.  Brand 1  Brand 2  Brand 3  Car 1 22.425.224.3 Car 2 1918.619.8 Car 3 24.62525.4 Car 4 23.523.624.1 Source  DF  SS  MS  F  p  Car 361.24920.41639.0330.000249 Gas 22.2221.1112.1240.200726 Error 63.1380.523 Total 1166.609\begin{array}{l}\begin{array} { l | l l l } & \text { Brand 1 } & \text { Brand 2 } & \text { Brand 3 } \\\hline \text { Car 1 } & 22.4 & 25.2 & 24.3 \\\text { Car 2 } & 19 & 18.6 & 19.8 \\\text { Car 3 } & 24.6 & 25 & 25.4 \\\text { Car 4 } & 23.5 & 23.6 & 24.1\end{array}\\\\\begin{array} { l r r r r c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Car } & 3 & 61.249 & 20.416 & 39.033 & 0.000249 \\\text { Gas } & 2 & 2.222 & 1.111 & 2.124 & 0.200726 \\\text { Error } & 6 & 3.138 & 0.523 & & \\\text { Total } & 11 & 66.609 & & &\end{array}\end{array}
Question
The following data shows the yield, in bushels per acre, categorized according to three varieties of corn and three different soil conditions. Test the null hypothesis of no interaction between variety and soil conditions at a significance level of 0.05.  Plot 1  Plot 2  Plot 3  Variety 1 156,167,162,160,145,151,170,162169,168148,155 Variety 2 172,176,179,186,161,162166,179160,176165,170 Variety 3 175,157,178,170,169,165,179,178172,174170,169\begin{array}{llll} & \text { Plot 1 } & \text { Plot 2 } & \text { Plot 3 } \\\text { Variety 1 } & 156,167, & 162,160, & 145,151, \\& 170,162 & 169,168 & 148,155 \\\text { Variety 2 } & 172,176, & 179,186, & 161,162 \text {, } \\& 166,179 & 160,176 & 165,170 \\\text { Variety 3 } & 175,157, & 178,170, & 169,165, \\& 179,178 & 172,174 & 170,169\end{array}
Question
The following data show annual income, in thousands of dollars, categorized according to the two factors of gender and level of education. Test the null hypothesis of no interaction between gender and level of education at a significance level of 0.05.  Female  Male  High school 23,27,24,2625,26,22,24 College 28,36,31,3335,32,39,28 Advanced degree 41,38,43,4935,50,47,44\begin{array} { l c c } & \text { Female } & \text { Male } \\\text { High school } & 23,27,24,26 & 25,26,22,24 \\\text { College } & 28,36,31,33 & 35,32,39,28 \\\text { Advanced degree } & 41,38,43,49 & 35,50,47,44\end{array}
Question
The following table shows the mileage for four different cars and three different brands of gas. Assuming no effect from the interaction between car and brand of gas, test the claim that the four cars have the same mean mileage. Use a 0.05 significance level.  Brand 1  Brand 2  Brand 3  Car 1 22.425.224.3 Car 2 1918.619.8 Car 3 24.62525.4 Car 4 23.523.624.1 Source  DF  SS  MS  F  p  Car 361.24920.41639.0330.000249 Gas 22.2221.1112.1240.200726 Error 63.1380.523 Total 1166.609\begin{array}{l}\begin{array} { l | l l l } & \text { Brand 1 } & \text { Brand 2 } & \text { Brand 3 } \\\hline \text { Car 1 } & 22.4 & 25.2 & 24.3 \\\text { Car 2 } & 19 & 18.6 & 19.8 \\\text { Car 3 } & 24.6 & 25 & 25.4 \\\text { Car 4 } & 23.5 & 23.6 & 24.1\end{array}\\\begin{array} { l r r r c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Car } & 3 & 61.249 & 20.416 & 39.033 & 0.000249 \\\text { Gas } & 2 & 2.222 & 1.111 & 2.124 & 0.200726 \\\text { Error } & 6 & 3.138 & 0.523 & & \\\text { Total } & 11 & 66.609 & & &\end{array}\end{array}
Question
The following Minitab display results from a study in which three different teachers taught calculus classes of five different sizes. The class average was recorded for each class. Assuming no effect from the interaction between teacher and class size, test the claim that the teacher has no effect on the class average. Use a 0.05 significance level.  Source  DF  SS  MS  F  p  Teacher 256.9328.471.0180.404 Class Size 4672.67168.176.0130.016 Error 8223.7327.97 Total 14953.33\begin{array} { l r r r c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Teacher } & 2 & 56.93 & 28.47 & 1.018 & 0.404 \\\text { Class Size } & 4 & 672.67 & 168.17 & 6.013 & 0.016 \\\text { Error } & 8 & 223.73 & 27.97 & & \\\text { Total } & 14 & 953.33 & & &\end{array}
Question
The following data contains task completion times, in minutes, categorized according to the gender of the machine operator and the machine used.
 malefemale Machine 1 15,1716,17Machine 214,1315,13 Machine 316,1817,19\begin{array} { l } & \text { male}& \text {female }\\ \text {Machine 1 }&15,17&16,17\\ \text {Machine 2}&14,13&15,13\\ \text { Machine 3}&16,18&17,19\\\end{array}
The ANOVA results lead us to conclude that the completion times are not affected by an interaction between machine and gender, and the times are not affected by gender, but they are affected by the machine. Change the table entries so that there is no effect from the interaction between machine and gender, there is no effect from the machine used, and there is no effect from the gender of the operator.
Question
The following results are from a statistics software package in which all of the F values and P-values are given. Is there a significant effect from the interaction? Should you test to see if there is a significant effect due to either A or B? If the answer is yes, is there a significant effect due to either A or B?  ANOVA Table  Source  DF  Sum squares  Mean square  F test  P-value A2164.02082.01025.010<.0001 B4230.78657.69718.002<.0001 Interaction 880.87910.1103.154.0031 Error 101323.7083.205 Total 115799.393\begin{array}{l}\text { ANOVA Table }\\\begin{array} { r | r | r | r | r | r } \text { Source } & \text { DF } & \text { Sum squares } & \text { Mean square } & \text { F test } & \text { P-value } \\\hline \mathrm { A } & 2 & 164.020 & 82.010 & 25.010 & < .0001 \\\mathrm {~B} & 4 & 230.786 & 57.697 & 18.002 & < .0001 \\\text { Interaction } & 8 & 80.879 & 10.110 & 3.154 & .0031 \\\text { Error } & 101 & 323.708 & 3.205 & & \\\text { Total } & 115 & 799.393 & & &\end{array}\end{array}
Question
The following results are from a statistics package in which all of the F values and P-values are given. Is there a significant effect from the interaction? Should you test to see if there is a significant effect due to either A or B? If the answer is yes, is there a significant effect due to either A or B?  ANoVA 1able  Source  DF  Sum squares  Mean square  F test  P-value A2415.87305207.936521.88259.1637 B32997.47186999.157299.04603.0001 Interaction 6707.26626117.877711.06723.3958 Error 465080.81667110.45254 Total 579201.42784\begin{array}{l}\text { ANoVA 1able }\\\begin{array} { r | r | r | r | r | r } \text { Source } & \text { DF } & \text { Sum squares } & \text { Mean square } & \text { F test } & \text { P-value } \\\hline \mathrm { A } & 2 & 415.87305 & 207.93652 & 1.88259 & .1637 \\\mathrm {~B} & 3 & 2997.47186 & 999.15729 & 9.04603 & .0001 \\\text { Interaction } & 6 & 707.26626 & 117.87771 & 1.06723 & .3958 \\\text { Error } & 46 & 5080.81667 & 110.45254 & & \\\text { Total } & 57 & 9201.42784 & & &\end{array}\end{array}
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Deck 12: Analysis of Variance
1
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-A consumer magazine wants to compare the lifetimes of ballpoint pens of three different types. The magazine takes a random sample of pens of each type in the following table.
 brandA brand B brand C 260181238218240257184162241219218213\begin{array}{lll}\text { brandA }&\text {brand B }&\text {brand C }\\\hline260 & 181 & 238 \\218 & 240 & 257 \\184 & 162 & 241 \\219 & 218 & 213\end{array}
Do the data indicate that there is a difference in mean lifetime for the three brands of ballpoint pens? Use  Use α=0.0\text { Use } \alpha = 0.0
Test statistic: F = 1.620. Critical value: F = 8.02. p-value:0.251.
Fail to reject the claim of equal means. The data do not provide sufficient evidence to conclude that there is a difference in the mean lifetimes of the three brands of ballpoint pen.
2
Provide an appropriate response.

-Describe the null and alternative hypotheses for one-way ANOVA. Give an example.
The null hypothesis for one-way ANOVA is that three or more means are equal. The alternative hypothesis is that the means are not all equal. Examples will vary.
3
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-The data below represent the weight losses for people on three different exercise programs.
 Exercise A Exercise BExercise C 2.55.84.38.84.96.27.31.15.89.87.88.15.11.27.9\begin{array}{lll}\text { Exercise A}&\text { Exercise B}& \text {Exercise C }\\\hline2.5 & 5.8 & 4.3 \\8.8 & 4.9 & 6.2 \\7.3 & 1.1 & 5.8 \\9.8 & 7.8 & 8.1 \\5.1 & 1.2 & 7.9\end{array}
At the 1% significance level, does it appear that a difference exists in the true mean weight loss produced by the three exercise programs?
Test statistic: F = 1.491. Critical value: F = 6.93. p-value:0.264.
Fail to reject the claim of equal means. The data do not provide sufficient evidence to conclude that there is a difference in the true mean weight loss produced by the three exercise programs.
4
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-At the 0.025 significance level, test the claim that the four brands have the same mean if the following sample results have been obtained.  brandA brand B brand C brand D 15202115251722152122201423231923221822202828\begin{array}{llll}\text { brandA }&\text {brand B }&\text {brand C }&\text {brand D }\\\hline15 & 20 & 21 & 15 \\25 & 17 & 22 & 15 \\21 & 22 & 20 & 14 \\23 & 23 & 19 & 23 \\22 & & 18 & 22 \\20 & & & 28\\&&&28\end{array}
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5
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  p  Factor 33010.001.60.264 Error 8506.25 Total 1180\begin{array} { l r c c c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Factor } & 3 & 30 & 10.00 & 1.6 & 0.264 \\\text { Error } & 8 & 50 & 6.25 & & \\\text { Total } & 11 & 80 & & &\end{array} Identify the value of the test statistic.

A)30
B)10.00
C)0.264
D)1.6
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6
Provide an appropriate response.
Provide an appropriate response.
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7
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  P  Factor 313.5004.5005.170.011 Error 1613.9250.870 Total 1927.425\begin{array} { l r c c c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { P } \\\text { Factor } & 3 & 13.500 & 4.500 & 5.17 & 0.011 \\\text { Error } & 16 & 13.925 & 0.870 & & \\\text { Total } & 19 & 27.425 & & &\end{array} Identify the value of the test statistic.

A)13.500
B)0.011
C)5.17
D)4.500
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8
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-Given the sample data below, test the claim that the populations have the same mean. Use a significance level of 0.05.  Brand A  Brand B  Brand C  Brand D n=16n=16n=16n=16xˉ=2.09xˉ=3.48xˉ=1.86xˉ=2.84s=0.37 s=0.61 s=0.45 s=0.53\begin{array} { l } \text { Brand A }& \text { Brand B } &\text { Brand C } & \text { Brand D } \\{ n = 16 } &{ n = 16 } & { n = 16 } &{ n = 16 } \\\bar { x } = 2.09& \bar { x } = 3.48 & \bar { x } = 1.86 & \bar { x } = 2.84 \\s = 0.37 & \mathrm {~s} = 0.61& \mathrm {~s} = 0.45 & \mathrm {~s} = 0.53 \\\end{array}
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9
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  p  Factor 313.5004.5005.170.011 Error 1613.9250.870 Total 1927.425\begin{array} { l r c c c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Factor } & 3 & 13.500 & 4.500 & 5.17 & 0.011 \\\text { Error } & 16 & 13.925 & 0.870 & & \\\text { Total } & 19 & 27.425 & & &\end{array} What can you conclude about the equality of the population means?

A)Accept the null hypothesis since the p-value is less than the significance level.
B)Reject the null hypothesis since the p-value is greater than the significance level.
C)Reject the null hypothesis since the p-value is less than the significance level.
D)Accept the null hypothesis since the p-value is greater than the significance level.
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10
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-Given the sample data below, test the claim that the populations have the same mean. Use a significance level of 0.05.  Brand A Brand B Brand Cn=10n=10n=10x=32.6x=31.7x=27.4 s2=4.51 s2=4.22 s2=4.69\begin{array}{ccc}\text { Brand } \mathrm{A} &\text { Brand } \mathrm{B} &\text { Brand } \mathrm{C}\\\hline\mathrm{n}=10 & \mathrm{n}=10 & \mathrm{n}=10 \\\overline{\mathrm{x}}=32.6 & \overline{\mathrm{x}}=31.7 & \overline{\mathrm{x}}=27.4 \\\mathrm{~s}^{2}=4.51 & \mathrm{~s}^{2}=4.22 & \mathrm{~s}^{2}=4.69\end{array}
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11
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  p  Factor 313.5004.5005.170.011 Error 1613.9250.870 Total 1927.425\begin{array} { l r c l c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Factor } & 3 & 13.500 & 4.500 & 5.17 & 0.011 \\\text { Error } & 16 & 13.925 & 0.870 & & \\\text { Total } & 19 & 27.425 & & &\end{array} Identify the p-value.

A)0.011
B)4.500
C)5.17
D)0.870
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12
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  p  Factor 33010.001.60.264 Error 8506.25 Total 1180\begin{array} { l r c c c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Factor } & 3 & 30 & 10.00 & 1.6 & 0.264 \\\text { Error } & 8 & 50 & 6.25 & & \\\text { Total } & 11 & 80 & & &\end{array} Find the critical value.

A)1.6
B)8.85
C)4.07
D)7.59
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13
Provide an appropriate response.

-  The test statistic for one-way ANOVA is F= variance between samples  variance within samples . Describe variance within samples and \text { The test statistic for one-way ANOVA is } F = \frac { \text { variance between samples } } { \text { variance within samples } } \text {. Describe variance within samples and } variance between samples. What relationship between variance within samples and variance between samples would result in the conclusion that the value of F is significant?
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14
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-Random samples of four different models of cars were selected and the gas mileage of each car was measured. The results are shown below.  Model A Model B Model C Model D 23283025252628262429322526302728\begin{array}{llll}\text { Model A }&\text {Model B }&\text {Model C }&\text {Model D }\\\hline23 & 28 & 30 & 25 \\25 & 26 & 28 & 26 \\24 & 29 & 32 & 25 \\26 & 30 & 27 & 28\end{array} Test the claim that the four different models have the same population mean. Use a significance level of 0.05.
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15
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-At the 0.025 significance level, test the claim that the three brands have the same mean if the following sample results have been obtained.  brand A brand B brand C 322722342425373332333022362139\begin{array}{lll}\text { brand A }&\text {brand B }&\text {brand C }&\\\hline32 & 27 & 22 \\34 & 24 & 25 \\37 & 33 & 32 \\33 & 30 & 22 \\36 & & 21 \\39 & &\end{array}
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16
Provide an appropriate response.

-When using statistical software packages, the critical value is typically not given. What method is used to determine whether you reject or fail to reject the null hypothesis?
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17
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  p  Factor 313.5004.5005.170.011 Error 1613.9250.870 Total 1927.425\begin{array} { l r c c c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Factor } & 3 & 13.500 & 4.500 & 5.17 & 0.011 \\\text { Error } & 16 & 13.925 & 0.870 & & \\\text { Total } & 19 & 27.425 & & &\end{array} Find the critical value.

A)3.24
B)8.70
C)5.42
D)3.06
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18
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  p  Factor 33010.001.60.264 Error 8506.25 Total 1180\begin{array} { l r c c c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Factor } & 3 & 30 & 10.00 & 1.6 & 0.264 \\\text { Error } & 8 & 50 & 6.25 & & \\\text { Total } & 11 & 80 & & &\end{array} Identify the p-value.

A)0.264
B)10.00
C)6.25
D)1.6
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19
Given below are the analysis of variance results from a Minitab display. Assume that you want to use a 0.05 significance level in testing the null hypothesis that the different samples come from populations with the same mean.

-  Source  DF  SS  MS  F  p  Factor 33010.001.60.264 Error 8506.25 Total 1180\begin{array} { l r c c c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Factor } & 3 & 30 & 10.00 & 1.6 & 0.264 \\\text { Error } & 8 & 50 & 6.25 & & \\\text { Total } & 11 & 80 & & &\end{array} What can you conclude about the equality of the population means?

A)Reject the null hypothesis since the p-value is less than the significance level.
B)Reject the null hypothesis since the p-value is greater than the significance level.
C)Accept the null hypothesis since the p-value is greater than the significance level.
D)Accept the null hypothesis since the p-value is less than the significance level.
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20
Test the claim that the samples come from populations with the same mean. Assume that the populations are normally distributed with the same variance.

-At the 0.025 significance level, test the claim that the four brands have the same mean if the following sample results have been obtained.  brandA brand B brand C brand D 1718212220182425212325272225262921262935293637\begin{array}{llll}\text { brandA }&\text {brand B }&\text {brand C }&\text {brand D }\\\hline17 & 18 & 21 & 22 \\20 & 18 & 24 & 25 \\21 & 23 & 25 & 27 \\22 & 25 & 26 & 29 \\21 & 26 & 29 & 35 \\& & 29 & 36 \\& & & 37\end{array}
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21
Provide an appropriate response.

-Fill in the missing entries in the following partially completed one-way ANOVA table.  Source  df  SS  MS=SS/df  F-statistic  Treatment 311.16 Error 13.720.686 Total \begin{array}{|l|r|r|l|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 3 & & & 11.16 \\\hline \text { Error } & & 13.72 & 0.686 & \\\hline \text { Total } & & & & \\\hline\end{array}

A)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 30.1840.06111.16 Error 2013.720.686 Total 2313.90\begin{array}{|l|r|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 3 & 0.184 & 0.061 & 11.16 \\\hline \text { Error } & 20 & 13.72 & 0.686 & \\\hline \text { Total } & 23 & 13.90 & & \\\hline\end{array}
B)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 322.977.6611.16 Error 2013.720.686 Total 2336.69\begin{array}{|l|r|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 3 & 22.97 & 7.66 & 11.16 \\\hline \text { Error } & 20 & 13.72 & 0.686 & \\\hline \text { Total } & 23 & 36.69 & & \\\hline\end{array}
C)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 348.8016.2711.16 Error 2013.720.686 Total 2362.52\begin{array}{|l|c|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 3 & 48.80 & 16.27 & 11.16 \\\hline \text { Error } & 20 & 13.72 & 0.686 & \\\hline \text { Total } & 23 & 62.52 & & \\\hline\end{array}
D)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 32.557.6611.16 Error 2013.720.686 Total 2316.27\begin{array}{|l|c|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 3 & 2.55 & 7.66 & 11.16 \\\hline \text { Error } & 20 & 13.72 & 0.686 & \\\hline \text { Total } & 23 & 16.27 & & \\\hline\end{array}
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22
At the same time each day, a researcher records the temperature in each of three greenhouses. The table shows the temperatures in degrees Fahrenheit recorded for one week.  Greenhouse #1  Greenhouse #2  Greenhouse #3 737167726963737262667261686560717362727159\begin{array} { c | c | c } \text { Greenhouse \#1 } & \text { Greenhouse \#2 } & \text { Greenhouse \#3 } \\\hline 73 & 71 & 67 \\72 & 69 & 63 \\73 & 72 & 62 \\66 & 72 & 61 \\68 & 65 & 60 \\71 & 73 & 62 \\72 & 71 & 59\end{array} i)Use a 0.05 significance level to test the claim that the average temperature is the same in each greenhouse. ii)How are the analysis of variance results affected if the same constant is added to every one of the original sample values?
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23
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 31,34,3229,23,2221,20,24 Machine  II 19,26,2235,33,3025,19,23 III 21,18,2620,23,2436,37,31 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 21.19.59 EMPLOYEE 25.852.93 INTERACTION 4710.81177.70 ERROR 18160.008.89 TOTAL 26877.85\begin{array}{l}\begin{array} { r r c c c } &&& { \text { Employee } } \\& & \text { A } & \text { B } & \text { C } \\& \text { I } & 31,34,32 & 29,23,22 & 21,20,24 \\\text { Machine } & \text { II } & 19,26,22 & 35,33,30 & 25,19,23 \\& \text { III } & 21,18,26 & 20,23,24 & 36,37,31\end{array}\\\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } & { \text { SS } } & \text { MS } \\\text { MACHINE } & 2 & 1.19 & .59 \\\text { EMPLOYEE } & 2 & 5.85 & 2.93 \\\text { INTERACTION } & 4 & 710.81 & 177.70 \\\text { ERROR } & 18 & 160.00 & 8.89 \\\text { TOTAL } & 26 & 877.85 &\end{array}\end{array} Assume that the number of items produced is not affected by an interaction between employee and machine. Using a 0.05 significance level, test the claim that the choice of employee has no effect on the number of items produced.
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24
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 16,18,1915,17,2014,18,16 Machine  II 20,27,2925,28,2729,28,26 III 15,18,1716,16,1913,17,16 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 2588.74294.37 EMPLOYEE 22.071.04 INTERACTION 415.483.87 ERROR 1898.675.48 TOTAL 26704.96\begin{array}{l}\begin{array} { r r c c c } & &&{ \text { Employee } } \\& & \text { A } & \text { B } & \text { C } \\& \text { I } & 16,18,19 & 15,17,20 & 14,18,16 \\\text { Machine } & \text { II } & 20,27,29 & 25,28,27 & 29,28,26 \\& \text { III } & 15,18,17 & 16,16,19 & 13,17,16\end{array}\\\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } &{ \text { SS } } &{ \text { MS } } \\\text { MACHINE } & 2 & 588.74 & 294.37 \\\text { EMPLOYEE } & 2 & 2.07 & 1.04 \\\text { INTERACTION } & 4 & 15.48 & 3.87 \\\text { ERROR } & 18 & 98.67 & 5.48 \\\text { TOTAL } & 26 & 704.96 &\end{array}\end{array} Assume that the number of items produced is not affected by an interaction between employee and machine. Using a 0.05 significance level, test the claim that the choice of employee has no effect on the number of items produced.
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25
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 31,34,3229,23,2221,20,24 Machine  II 19,26,2235,33,3025,19,23 III 21,18,2620,23,2436,37,31 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 21.19.59 EMPLOYEE 25.852.93 INTERACTION 4710.81177.70 ERROR 18160.008.89 TOTAL 26877.85\begin{array}{l}\begin{array} { r r c c c } && { \text { Employee } } \\&& { \text { A } } & \text { B } & \text { C } \\& \text { I } & 31,34,32 & 29,23,22 & 21,20,24 \\\text { Machine } & \text { II } & 19,26,22 & 35,33,30 & 25,19,23 \\& \text { III } & 21,18,26 & 20,23,24 & 36,37,31\end{array}\\\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } & { \text { SS } } & \text { MS } \\\text { MACHINE } & 2 & 1.19 & .59 \\\text { EMPLOYEE } & 2 & 5.85 & 2.93 \\\text { INTERACTION } & 4 & 710.81 & 177.70 \\\text { ERROR } & 18 & 160.00 & 8.89 \\\text { TOTAL } & 26 & 877.85 &\end{array}\end{array} Using a 0.05 significance level, test the claim that the interaction between employee and machine has no effect on the number of items produced.
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26
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 23,27,2930,27,2518,20,22 Machine II 25,26,2424,29,2619,16,14 III 28,25,2625,27,2315,11,17 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 234.6717.33 EMPLOYEE 2504.67252.33 INTERACTION 426.676.67 ERROR 1898.005.44 TOTAL 26664.00\begin{array}{l}\begin{array}{rccc} &&\text { Employee }\\& \text { A } & \text { B } & \text { C } \\\text { I } & 23,27,29 & 30,27,25 & 18,20,22 \\\text { Machine II } & 25,26,24 & 24,29,26 & 19,16,14 \\\text { III } & 28,25,26 & 25,27,23 & 15,11,17\end{array}\\\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } & { \text { SS } } & { \text { MS } } \\\text { MACHINE } & 2 & 34.67 & 17.33 \\\text { EMPLOYEE } & 2 & 504.67 & 252.33 \\\text { INTERACTION } & 4 & 26.67 & 6.67 \\\text { ERROR } & 18 & 98.00 & 5.44 \\\text { TOTAL } & 26 & 664.00 &\end{array}\end{array} Assume that the number of items produced is not affected by an interaction between employee and machine. Using a 0.05 significance level, test the claim that the choice of employee has no effect on the number of items produced.
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27
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.
 Employee  A  B  C  Machine  II 16,18,1915,17,2014,18,16 II 20,27,2925,28,2729,28,26 III 15,18,1716,16,1913,17,16\begin{array}{rrccc} &&&{\text { Employee }} \\& & \text { A } & \text { B } & \text { C } \\\text { Machine } & \text { II } & 16,18,19 & 15,17,20 & 14,18,16 \\& \text { II } & 20,27,29 & 25,28,27 & 29,28,26 \\& \text { III } & 15,18,17 & 16,16,19 & 13,17,16\end{array}

 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 2588.74294.37 EMPLOYEE 22.071.04 INTERACTION 415.483.87 ERROR 1898.675.48 TOTAL 26704.96\begin{array}{l}\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array}{lrrr}\text { SOURCE } & \text { DF } &{\text { SS }} & {\text { MS }} \\\text { MACHINE } & 2 & 588.74 & 294.37 \\\text { EMPLOYEE } & 2 & 2.07 & 1.04 \\\text { INTERACTION } & 4 & 15.48 & 3.87 \\\text { ERROR } & 18 & 98.67 & 5.48 \\\text { TOTAL } & 26 & 704.96 &\end{array}\end{array}
Using a 0.05 significance level, test the claim that the interaction between employee and machine has no effect on the number of items produced.
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28
Six independent samples of 100 values each are randomly drawn from populations that are normally distributed with equal variances. You wish to test the claim that μ1=μ2=μ3=μ4=μ5=μ6\mu _ { 1 } = \mu _ { 2 } = \mu _ { 3 } = \mu _ { 4 } = \mu _ { 5 } = \mu _ { 6 } .
If you test the individual claims μ1=μ2,μ1=μ3,μ1=μ4,,μ5=μ6\mu _ { 1 } = \mu _ { 2 } , \mu _ { 1 } = \mu _ { 3 } , \mu _ { 1 } = \mu _ { 4 } , \ldots , \mu _ { 5 } = \mu _ { 6 } , how many ways can you pair off the means?
i) Assume that the tests are independent and that for each test of equality between two means, there is a 0.900.90 probability of not making a type I error. If all possible pairs of means are tested for equality, what is the probabi making no type I errors?
ii) If you use analysis of variance to test the claim that μ1=μ2=μ3=μ4=μ5=μ6\mu _ { 1 } = \mu _ { 2 } = \mu _ { 3 } = \mu _ { 4 } = \mu _ { 5 } = \mu _ { 6 } at the 0.100.10 level of significan what is the probability of not making a type I error?
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29
Four independent samples of 100 values each are randomly drawn from populations that are normally distributed with equal variances. You wish to test the claim that μ1=μ2=μ3=μ4\mu _ { 1 } = \mu _ { 2 } = \mu _ { 3 } = \mu _ { 4 } .
If you test the individual claims μ1=μ2,μ1=μ3,μ1=μ4,,μ3=μ4\mu _ { 1 } = \mu _ { 2 } , \mu _ { 1 } = \mu _ { 3 } , \mu _ { 1 } = \mu _ { 4 } , \ldots , \mu _ { 3 } = \mu _ { 4 } , how many ways can you pair off the means?
ii) Assume that the tests are independent and that for each test of equality between two means, there is a 0.990.99 probability of not making a type I error. If all possible pairs of means are tested for equality, what is the probabi making no type I errors?
iii) If you use analysis of variance to test the claim that μ1=μ2=μ3=μ4\mu _ { 1 } = \mu _ { 2 } = \mu _ { 3 } = \mu _ { 4 } at the 0.010.01 level of significance, what is the probability of not making a type I error?
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30
The following table entries are the times in seconds for three different drivers racing on four different tracks. Assuming no effect from the interaction between driver and track, test the claim that the three drivers have the same mean time. Use a 0.05 significance level.  Track 1  Track 2  Track 3  Track 4  Driver 1 72706871 Driver 2 74716672 Driver 3 76696470\begin{array}{c|cccc} & \text { Track 1 } & \text { Track 2 } & \text { Track 3 } & \text { Track 4 } \\\hline \text { Driver 1 } & 72 & 70 & 68 & 71 \\\text { Driver 2 } & 74 & 71 & 66 & 72 \\\text { Driver 3 } & 76 & 69 & 64 & 70\end{array}
 Source  DF  SS  MS  F  p  Driver 2210.330.729 Track 398.2532.7510.920.00763 Error 6183 Total 11118.25\begin{array} { l r c l r c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Driver } & 2 & 2 & 1 & 0.33 & 0.729 \\\text { Track } & 3 & 98.25 & 32.75 & 10.92 & 0.00763 \\\text { Error } & 6 & 18 & 3 & & \\\text { Total } & 11 & 118.25 & & &\end{array}
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31
At the same time each day, a researcher records the temperature in each of three greenhouses. The table shows the temperatures in degrees Fahrenheit recorded for one week.  Greenhouse #1  Greenhouse #2  Greenhouse # 737167726963737262667261686560717362727159\begin{array} { c | c | c } \text { Greenhouse \#1 } & \text { Greenhouse \#2 } & \text { Greenhouse \# } \\\hline 73 & 71 & 67 \\72 & 69 & 63 \\73 & 72 & 62 \\66 & 72 & 61 \\68 & 65 & 60 \\71 & 73 & 62 \\72 & 71 & 59\end{array} i)Use a 0.05 significance level to test the claim that the average temperature is the same in each greenhouse. ii)How are the analysis of variance results affected if 8° is added to each temperature listed for greenhouse #3?
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32
Provide an appropriate response.

-Fill in the missing entries in the following partially completed one-way ANOVA table.  Source  df  SS  MS=SS/df  F-statistic  Treatment 25.2 Error 243.5 Total 28\begin{array}{|l|c|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & & 25.2 & & \\\hline \text { Error } & 24 & & 3.5 & \\\hline \text { Total } & 28 & & & \\\hline\end{array}

A)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 425.26.301.80 Error 2484.03.5 Total 2825.35\begin{array}{|l|c|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 4 & 25.2 & 6.30 & 1.80 \\\hline \text { Error } & 24 & 84.0 & 3.5 & \\\hline \text { Total } & 28 & 25.35 & & \\\hline\end{array}
B)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 425.26.300.56 Error 2484.03.5 Total 28109.2\begin{array}{|l|c|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 4 & 25.2 & 6.30 & 0.56 \\\hline \text { Error } & 24 & 84.0 & 3.5 & \\\hline \text { Total } & 28 & 109.2 & & \\\hline\end{array}
C)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 425.26.301.80 Error 2484.03.5 Total 28109.2\begin{array}{|l|c|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 4 & 25.2 & 6.30 & 1.80 \\\hline \text { Error } & 24 & 84.0 & 3.5 & \\\hline \text { Total } & 28 & 109.2 & & \\\hline\end{array}
D)
 Source  df  SS  MS=SS/df  F-statistic  Treatment 5225.20.48374.40 Error 2484.03.5 Total 28109.2\begin{array}{|l|c|c|c|c|}\hline \text { Source } & \text { df } & \text { SS } & \text { MS=SS/df } & \text { F-statistic } \\\hline \text { Treatment } & 52 & 25.2 & 0.48 & 374.40 \\\hline \text { Error } & 24 & 84.0 & 3.5 & \\\hline \text { Total } & 28 & 109.2 & & \\\hline\end{array}
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33
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 23,27,2930,27,2518,20,22 Machine  II 25,26,2424,29,2619,16,14 III 28,25,2625,27,2315,11,17 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 234.6717.33 EMPLOYEE 2504.67252.33 INTERACTION 426.676.67 ERROR 1898.005.44 TOTAL 26664.00\begin{array}{l}\begin{array} { r r r c c } &&&{ \text { Employee } } \\& & \text { A } & \text { B } & \text { C } \\& \text { I } & 23,27,29 & 30,27,25 & 18,20,22 \\\text { Machine } & \text { II } & 25,26,24 & 24,29,26 & 19,16,14 \\& \text { III } & 28,25,26 & 25,27,23 & 15,11,17\end{array}\\\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } & { \text { SS } } & { \text { MS } } \\\text { MACHINE } & 2 & 34.67 & 17.33 \\\text { EMPLOYEE } & 2 & 504.67 & 252.33 \\\text { INTERACTION } & 4 & 26.67 & 6.67 \\\text { ERROR } & 18 & 98.00 & 5.44 \\\text { TOTAL } & 26 & 664.00 &\end{array}\end{array} Using a 0.05 significance level, test the claim that the interaction between employee and machine has no effect on the number of items produced.
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34
The following table entries are test scores for males and females at different times of day. Assuming no effect from the interaction between gender and test time, test the claim that males and females perform the same on the test. Use a 0.05 significance level. 6 a.m. - 9 a.m. 9 a.m. 12 p.m. 12 p.m. - 3 p.m. 3p.m.6 p.m.  Male 87899285 Female 72849489 Source  DF  SS  MS  F  p  Gender 124.524.50.66520.4745 Time 3183611.65610.3444 Error 3110.536.83 Total 7318\begin{array}{l}\begin{array} { l | c c c c } & 6 \text { a.m. - } 9 \text { a.m. } &9 \text { a.m. } - 12 \text { p.m. } &12 \text { p.m. - 3 p.m. } &3 p.m. - 6 \text { p.m. } \\\hline \text { Male } & 87 & 89 & 92 & 85 \\\text { Female } & 72 & 84 & 94 & 89\end{array}\\\begin{array} { l c c l c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Gender } & 1 & 24.5 & 24.5 & 0.6652 & 0.4745 \\\text { Time } & 3 & 183 & 61 & 1.6561 & 0.3444 \\\text { Error } & 3 & 110.5 & 36.83 & & \\\text { Total } & 7 & 318 & & &\end{array}\end{array}
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35
The following table entries are the times in seconds for three different drivers racing on four different tracks. Assuming no effect from the interaction between driver and track, test the claim that the track has no effect on the time. Use a 0.05 significance level.  Track 1  Track 2  Track 3  Track 4  Driver 1 72706871 Driver 2 74716672 Driver 3 76696470 Source  DF  SS  MS  F  p  Driver 2210.330.729 Track 398.2532.7510.920.00763 Error 6183 Total 11118.25\begin{array}{l}\begin{array} { c | c c c c } & \text { Track 1 } & \text { Track 2 } & \text { Track 3 } & \text { Track 4 } \\\hline \text { Driver 1 } & 72 & 70 & 68 & 71 \\\text { Driver 2 } & 74 & 71 & 66 & 72 \\\text { Driver 3 } & 76 & 69 & 64 & 70\end{array}\\\\\begin{array} { l r c l r l } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Driver } & 2 & 2 & 1 & 0.33 & 0.729 \\\text { Track } & 3 & 98.25 & 32.75 & 10.92 & 0.00763 \\\text { Error } & 6 & 18 & 3 & & \\\text { Total } & 11 & 118.25 & & &\end{array}\end{array}
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36
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 31,34,3229,23,2221,20,24 Machine  II 19,26,2235,33,3025,19,23 III 21,18,2620,23,2436,37,31 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 21.19.59 EMPLOYEE 25.852.93 INTERACTION 4710.81177.70 ERROR 18160.008.89 TOTAL 26877.85\begin{array}{l}\begin{array} { r r c c c } &&&{ \text { Employee } } \\& & \text { A } & \text { B } & \text { C } \\& \text { I } & 31,34,32 & 29,23,22 & 21,20,24 \\\text { Machine } & \text { II } & 19,26,22 & 35,33,30 & 25,19,23 \\& \text { III } & 21,18,26 & 20,23,24 & 36,37,31\end{array}\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } & { \text { SS } } & \text { MS } \\\text { MACHINE } & 2 & 1.19 & .59 \\\text { EMPLOYEE } & 2 & 5.85 & 2.93 \\\text { INTERACTION } & 4 & 710.81 & 177.70 \\\text { ERROR } & 18 & 160.00 & 8.89 \\\text { TOTAL } & 26 & 877.85 &\end{array}\end{array} Assume that the number of items produced is not affected by an interaction between employee and machine. Using a 0.05 significance level, test the claim that the machine has no effect on the number of items produced.
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37
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 16,18,1915,17,2014,18,16 Machine  II 20,27,2925,28,2729,28,26 III 15,18,1716,16,1913,17,16 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 2588.74294.37 EMPLOYEE 22.071.04 INTERACTION 415.483.87 ERROR 1898.675.48 TOTAL 26704.96\begin{array}{l}\begin{array} { r r c c c } & && { \text { Employee } } \\& & \text { A } & \text { B } & \text { C } \\& \text { I } & 16,18,19 & 15,17,20 & 14,18,16 \\\text { Machine } & \text { II } & 20,27,29 & 25,28,27 & 29,28,26 \\& \text { III } & 15,18,17 & 16,16,19 & 13,17,16\end{array}\\\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } & { \text { SS } } & { \text { MS } } \\\text { MACHINE } & 2 & 588.74 & 294.37 \\\text { EMPLOYEE } & 2 & 2.07 & 1.04 \\\text { INTERACTION } & 4 & 15.48 & 3.87 \\\text { ERROR } & 18 & 98.67 & 5.48 \\\text { TOTAL } & 26 & 704.96 &\end{array}\end{array} Assume that the number of items produced is not affected by an interaction between employee and machine. Using a 0.05 significance level, test the claim that the machine has no effect on the number of items produced.
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38
Use the data given below to verify that the t test for independent samples and the ANOVA method are equivalent. AB101929181127193015181621\begin{array} { c | c } \mathrm { A } & \mathrm { B } \\\hline 10 & 19 \\29 & 18 \\11 & 27 \\19 & 30 \\15 & 18 \\16 & 21\end{array} i)Use a t test with a 0.05 significance level to test the claim that the two samples come from populations with the same means. ii)Use the ANOVA method with a 0.05 significance level to test the same claim. iii)Verify that the squares of the t test statistic and the critical value are equal to the F test statistic and critical value.
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39
Use the data given below to verify that the t test for independent samples and the ANOVA method are equivalent. AB85748172736591836459\begin{array} { c | c } \mathrm { A } & \mathrm { B } \\\hline 85 & 74 \\81 & 72 \\73 & 65 \\91 & 83 \\64 & 59\end{array} i)Use a t test with a 0.05 significance level to test the claim that the two samples come from populations with the same means. ii)Use the ANOVA method with a 0.05 significance level to test the same claim. iii)Verify that the squares of the t test statistic and the critical value are equal to the F test statistic and critical value.
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40
A manager records the production output of three employees who each work on three different machines for three different days. The sample results are given below and the Minitab results follow.  Employee  A  B  C  I 23,27,2930,27,2518,20,22 Machine  II 25,26,2424,29,2619,16,14 III 28,25,2625,27,2315,11,17 ANALYSIS OF VARIANCE ITEMS  SOURCE  DF  SS  MS  MACHINE 234.6717.33 EMPLOYEE 2504.67252.33 INTERACTION 426.676.67 ERROR 1898.005.44 TOTAL 26664.00\begin{array}{l}\begin{array} { l r c c c } & &&{ \text { Employee } } \\&& { \text { A } } & \text { B } & \text { C } \\& \text { I } & 23,27,29 & 30,27,25 & 18,20,22 \\\text { Machine } & \text { II } & 25,26,24 & 24,29,26 & 19,16,14 \\& \text { III } & 28,25,26 & 25,27,23 & 15,11,17\end{array}\\\\\text { ANALYSIS OF VARIANCE ITEMS }\\\begin{array} { l r r r } \text { SOURCE } & \text { DF } & { \text { SS } } & \text { MS } \\\text { MACHINE } & 2 & 34.67 & 17.33 \\\text { EMPLOYEE } & 2 & 504.67 & 252.33 \\\text { INTERACTION } & 4 & 26.67 & 6.67 \\\text { ERROR } & 18 & 98.00 & 5.44 \\\text { TOTAL } & 26 & 664.00 &\end{array}\end{array} Assume that the number of items produced is not affected by an interaction between employee and machine. Using a 0.05 significance level, test the claim that the machine has no effect on the number of items produced.
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41
The following data contains task completion times, in minutes, categorized according to the gender of the machine operator and the machine used.
 malefemale Machine 1 15,1716,17Machine 214,1315,13 Machine 316,1817,19\begin{array} { l } & \text { male}& \text {female }\\ \text {Machine 1 }&15,17&16,17\\ \text {Machine 2}&14,13&15,13\\ \text { Machine 3}&16,18&17,19\\\end{array}
Assume that two-way ANOVA is used to analyze the data. How are the ANOVA results affected if the first sample value in the first cell is changed to 30 minutes?
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42
The following data shows annual income, in thousands of dollars, categorized according to the two factors of gender and level of education. Assume that incomes are not affected by an interaction between gender and level of education, and test the null hypothesis that gender has no effect on income. Use a 0.05 significance level.  Female  Male  High school 23,27,24,2625,26,22,24 College 28,36,31,3335,32,39,28 Advanced degree 41,38,43,4935,50,47,44\begin{array} { l c c } & \text { Female } & \text { Male } \\\text { High school } & 23,27,24,26 & 25,26,22,24 \\\text { College } & 28,36,31,33 & 35,32,39,28 \\\text { Advanced degree } & 41,38,43,49 & 35,50,47,44\end{array}
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43
The following data shows the yield, in bushels per acre, categorized according to three varieties of corn and three different soil conditions. Assume that yields are not affected by an interaction between variety and soil conditions, and test the null hypothesis that soil conditions have no effect on yield. Use a 0.05 significance level.  Plot 1  Plot 2  Plot 3  Variety 1 156,167,162,160,145,151170,162169,168148,155 Variety 2 172,176,179,186,161,162,166,179160,176165,170 Variety 3 175,157,178,170,169,165,179,178172,174170,169\begin{array}{cccc} & \text { Plot 1 } & \text { Plot 2 } & \text { Plot 3 } \\\text { Variety 1 } & 156,167, & 162,160, & 145,151 \text {, } \\& 170,162 & 169,168 & 148,155 \\\text { Variety 2 } & 172,176, & 179,186, & 161,162, \\& 166,179 & 160,176 & 165,170 \\\text { Variety 3 } & 175,157, & 178,170, & 169,165, \\& 179,178 & 172,174 & 170,169\end{array}
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44
The following data contains task completion times, in minutes, categorized according to the gender of the machine operator and the machine used.
 malefemale Machine 1 15,1716,17Machine 214,1315,13 Machine 316,1817,19\begin{array} { l } & \text { male}& \text {female }\\ \text {Machine 1 }&15,17&16,17\\ \text {Machine 2}&14,13&15,13\\ \text { Machine 3}&16,18&17,19\\\end{array}
The ANOVA results lead us to conclude that the completion times are not affected by an interaction between machine and gender, and the times are not affected by gender, but they are affected by the machine. Change the table entries so that there is no effect from the interaction between machine and gender, but there is an effect from the gender of the operator.
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45
The following data contains task completion times, in minutes, categorized according to the gender of the machine operator and the machine used.
 Male  Female  Machine 1 15,1716,17 Machine 2 14,1315,13 Machine 3 16,1817,19\begin{array}{lrl} & \text { Male } & \text { Female } \\\text { Machine 1 } & 15,17 & 16,17 \\\text { Machine 2 } & 14,13 & 15,13 \\\text { Machine 3 } & 16,18 & 17,19\end{array}
Assume that two-way ANOVA is used to analyze the data. How are the ANOVA results affected if the times are all doubled?
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46
The following data contains task completion times, in minutes, categorized according to the gender of the machine operator and the machine used.
 Male  Female  Machine 1 15,1716,17 Machine 2 14,1315,13 Machine 3 16,1817,19\begin{array}{lrl} & \text { Male } & \text { Female } \\\text { Machine 1 } & 15,17 & 16,17 \\\text { Machine 2 } & 14,13 & 15,13 \\\text { Machine 3 } & 16,18 & 17,19\end{array}
Assume that two-way ANOVA is used to analyze the data. How are the ANOVA results affected if 5 minutes is added to each completion time?
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47
The following data contains task completion times, in minutes, categorized according to the gender of the machine operator and the machine used.
 Male  Female  Machine 1 15,1716,17 Machine 2 14,1315,13 Machine 3 16,1817,19\begin{array}{lrl} & \text { Male } & \text { Female } \\\text { Machine 1 } & 15,17 & 16,17 \\\text { Machine 2 } & 14,13 & 15,13 \\\text { Machine 3 } & 16,18 & 17,19\end{array}
Assume that two-way ANOVA is used to analyze the data. How are the ANOVA results affected if the times are converted to hours?
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48
The following data shows the yield, in bushels per acre, categorized according to three varieties of corn and three different soil conditions. Assume that yields are not affected by an interaction between variety and soil conditions, and test the null hypothesis that variety has no effect on yield. Use a 0.05 significance level.
 Plot 1  Plot 2  Plot 3  Variety 1 156,167,162,160,145,151170,162169,168148,155 Variety 2 172,176,179,186,161,162166,179160,176165,170 Variety 3 175,157,178,170,169,165179,178172,174170,169\begin{array}{clcc} & \text { Plot 1 } & \text { Plot 2 } & \text { Plot 3 } \\\text { Variety 1 } & 156,167, & 162,160, & 145,151 \\& 170,162 & 169,168 & 148,155 \\\text { Variety 2 } & 172,176, & 179,186, & 161,162 \\& 166,179 & 160,176 & 165,170 \\\text { Variety 3 } & 175,157, & 178,170, & 169,165 \\& 179,178 & 172,174 & 170,169\end{array}
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49
The following data shows annual income, in thousands of dollars, categorized according to the two factors of gender and level of education. Assume that incomes are not affected by an interaction between gender and level of education, and test the null hypothesis that level of education has no effect on income. Use a 0.05 significance level.  Female  Male  High school 23,27,24,2625,26,22,24 College 28,36,31,3335,32,39,28 Advanced degree 41,38,43,4935,50,47,44\begin{array} { l c c } & \text { Female } & \text { Male } \\\text { High school } & 23,27,24,26 & 25,26,22,24 \\\text { College } & 28,36,31,33 & 35,32,39,28 \\\text { Advanced degree } & 41,38,43,49 & 35,50,47,44\end{array}
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50
The following table entries are test scores for males and females at different times of day. Assuming no effect from the interaction between gender and test time, test the claim that time of day does not affect test scores. Use a 0.05 significance level. 6 a.m. 9 a.m. 9 a.m. 12 p.m. 12 p.m. 3 p.m.3p.m.6 p.m.  Male 87899285 Female 72849489 Source  DF  SS  MS  F  p  Gender 124.524.50.66520.4745 Time 3183611.65610.3444 Error 3110.536.83 Total 7318\begin{array}{l}\begin{array} { l | c c c c } & 6 \text { a.m. } - 9 \text { a.m. } &9 \text { a.m. } - 12 \text { p.m. } &12 \text { p.m. } - 3 \text { p.m.}& 3 p.m. - 6 \text { p.m. } \\\hline \text { Male } & 87 & 89 & 92 & 85 \\\text { Female } & 72 & 84 & 94 & 89\end{array}\\\begin{array} { l c l l c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Gender } & 1 & 24.5 & 24.5 & 0.6652 & 0.4745 \\\text { Time } & 3 & 183 & 61 & 1.6561 & 0.3444 \\\text { Error } & 3 & 110.5 & 36.83 & & \\\text { Total } & 7 & 318 & & &\end{array}\end{array}
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51
The following Minitab display results from a study in which three different teachers taught calculus classes of five different sizes. The class average was recorded for each class. Assuming no effect from the interaction between teacher and class size, test the claim that class size has no effect on the class average. Use a 0.05 significance level.  Source  DF  SS  MS  F  p  Teacher 256.9328.471.0180.404 Class Size 4672.67168.176.0130.016 Error 8223.7327.97 Total 14953.33\begin{array} { l r r r c c } \text { Source } & \text { DF } & \text { SS } & { \text { MS } } & \text { F } & \text { p } \\\text { Teacher } & 2 & 56.93 & 28.47 & 1.018 & 0.404 \\\text { Class Size } & 4 & 672.67 & 168.17 & 6.013 & 0.016 \\\text { Error } & 8 & 223.73 & 27.97 & & \\\text { Total } & 14 & 953.33 & & &\end{array}
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52
The following data contains task completion times, in minutes, categorized according to the gender of the machine operator and the machine used.
 malefemale Machine 1 15,1716,17Machine 214,1315,13 Machine 316,1817,19\begin{array} { l } & \text { male}& \text {female }\\ \text {Machine 1 }&15,17&16,17\\ \text {Machine 2}&14,13&15,13\\ \text { Machine 3}&16,18&17,19\\\end{array}
The ANOVA results lead us to conclude that the completion times are not affected by an interaction between machine and gender, and the times are not affected by gender, but they are affected by the machine. Change the table entries so that there is an effect from the interaction between machine and gender.
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53
The following table shows the mileage for four different cars and three different brands of gas. Assuming no effect from the interaction between car and brand of gas, test the claim that the three brands of gas provide the same mean gas mileage. Use a 0.05 significance level.  Brand 1  Brand 2  Brand 3  Car 1 22.425.224.3 Car 2 1918.619.8 Car 3 24.62525.4 Car 4 23.523.624.1 Source  DF  SS  MS  F  p  Car 361.24920.41639.0330.000249 Gas 22.2221.1112.1240.200726 Error 63.1380.523 Total 1166.609\begin{array}{l}\begin{array} { l | l l l } & \text { Brand 1 } & \text { Brand 2 } & \text { Brand 3 } \\\hline \text { Car 1 } & 22.4 & 25.2 & 24.3 \\\text { Car 2 } & 19 & 18.6 & 19.8 \\\text { Car 3 } & 24.6 & 25 & 25.4 \\\text { Car 4 } & 23.5 & 23.6 & 24.1\end{array}\\\\\begin{array} { l r r r r c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Car } & 3 & 61.249 & 20.416 & 39.033 & 0.000249 \\\text { Gas } & 2 & 2.222 & 1.111 & 2.124 & 0.200726 \\\text { Error } & 6 & 3.138 & 0.523 & & \\\text { Total } & 11 & 66.609 & & &\end{array}\end{array}
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54
The following data shows the yield, in bushels per acre, categorized according to three varieties of corn and three different soil conditions. Test the null hypothesis of no interaction between variety and soil conditions at a significance level of 0.05.  Plot 1  Plot 2  Plot 3  Variety 1 156,167,162,160,145,151,170,162169,168148,155 Variety 2 172,176,179,186,161,162166,179160,176165,170 Variety 3 175,157,178,170,169,165,179,178172,174170,169\begin{array}{llll} & \text { Plot 1 } & \text { Plot 2 } & \text { Plot 3 } \\\text { Variety 1 } & 156,167, & 162,160, & 145,151, \\& 170,162 & 169,168 & 148,155 \\\text { Variety 2 } & 172,176, & 179,186, & 161,162 \text {, } \\& 166,179 & 160,176 & 165,170 \\\text { Variety 3 } & 175,157, & 178,170, & 169,165, \\& 179,178 & 172,174 & 170,169\end{array}
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55
The following data show annual income, in thousands of dollars, categorized according to the two factors of gender and level of education. Test the null hypothesis of no interaction between gender and level of education at a significance level of 0.05.  Female  Male  High school 23,27,24,2625,26,22,24 College 28,36,31,3335,32,39,28 Advanced degree 41,38,43,4935,50,47,44\begin{array} { l c c } & \text { Female } & \text { Male } \\\text { High school } & 23,27,24,26 & 25,26,22,24 \\\text { College } & 28,36,31,33 & 35,32,39,28 \\\text { Advanced degree } & 41,38,43,49 & 35,50,47,44\end{array}
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56
The following table shows the mileage for four different cars and three different brands of gas. Assuming no effect from the interaction between car and brand of gas, test the claim that the four cars have the same mean mileage. Use a 0.05 significance level.  Brand 1  Brand 2  Brand 3  Car 1 22.425.224.3 Car 2 1918.619.8 Car 3 24.62525.4 Car 4 23.523.624.1 Source  DF  SS  MS  F  p  Car 361.24920.41639.0330.000249 Gas 22.2221.1112.1240.200726 Error 63.1380.523 Total 1166.609\begin{array}{l}\begin{array} { l | l l l } & \text { Brand 1 } & \text { Brand 2 } & \text { Brand 3 } \\\hline \text { Car 1 } & 22.4 & 25.2 & 24.3 \\\text { Car 2 } & 19 & 18.6 & 19.8 \\\text { Car 3 } & 24.6 & 25 & 25.4 \\\text { Car 4 } & 23.5 & 23.6 & 24.1\end{array}\\\begin{array} { l r r r c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Car } & 3 & 61.249 & 20.416 & 39.033 & 0.000249 \\\text { Gas } & 2 & 2.222 & 1.111 & 2.124 & 0.200726 \\\text { Error } & 6 & 3.138 & 0.523 & & \\\text { Total } & 11 & 66.609 & & &\end{array}\end{array}
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57
The following Minitab display results from a study in which three different teachers taught calculus classes of five different sizes. The class average was recorded for each class. Assuming no effect from the interaction between teacher and class size, test the claim that the teacher has no effect on the class average. Use a 0.05 significance level.  Source  DF  SS  MS  F  p  Teacher 256.9328.471.0180.404 Class Size 4672.67168.176.0130.016 Error 8223.7327.97 Total 14953.33\begin{array} { l r r r c c } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { p } \\\text { Teacher } & 2 & 56.93 & 28.47 & 1.018 & 0.404 \\\text { Class Size } & 4 & 672.67 & 168.17 & 6.013 & 0.016 \\\text { Error } & 8 & 223.73 & 27.97 & & \\\text { Total } & 14 & 953.33 & & &\end{array}
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58
The following data contains task completion times, in minutes, categorized according to the gender of the machine operator and the machine used.
 malefemale Machine 1 15,1716,17Machine 214,1315,13 Machine 316,1817,19\begin{array} { l } & \text { male}& \text {female }\\ \text {Machine 1 }&15,17&16,17\\ \text {Machine 2}&14,13&15,13\\ \text { Machine 3}&16,18&17,19\\\end{array}
The ANOVA results lead us to conclude that the completion times are not affected by an interaction between machine and gender, and the times are not affected by gender, but they are affected by the machine. Change the table entries so that there is no effect from the interaction between machine and gender, there is no effect from the machine used, and there is no effect from the gender of the operator.
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59
The following results are from a statistics software package in which all of the F values and P-values are given. Is there a significant effect from the interaction? Should you test to see if there is a significant effect due to either A or B? If the answer is yes, is there a significant effect due to either A or B?  ANOVA Table  Source  DF  Sum squares  Mean square  F test  P-value A2164.02082.01025.010<.0001 B4230.78657.69718.002<.0001 Interaction 880.87910.1103.154.0031 Error 101323.7083.205 Total 115799.393\begin{array}{l}\text { ANOVA Table }\\\begin{array} { r | r | r | r | r | r } \text { Source } & \text { DF } & \text { Sum squares } & \text { Mean square } & \text { F test } & \text { P-value } \\\hline \mathrm { A } & 2 & 164.020 & 82.010 & 25.010 & < .0001 \\\mathrm {~B} & 4 & 230.786 & 57.697 & 18.002 & < .0001 \\\text { Interaction } & 8 & 80.879 & 10.110 & 3.154 & .0031 \\\text { Error } & 101 & 323.708 & 3.205 & & \\\text { Total } & 115 & 799.393 & & &\end{array}\end{array}
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60
The following results are from a statistics package in which all of the F values and P-values are given. Is there a significant effect from the interaction? Should you test to see if there is a significant effect due to either A or B? If the answer is yes, is there a significant effect due to either A or B?  ANoVA 1able  Source  DF  Sum squares  Mean square  F test  P-value A2415.87305207.936521.88259.1637 B32997.47186999.157299.04603.0001 Interaction 6707.26626117.877711.06723.3958 Error 465080.81667110.45254 Total 579201.42784\begin{array}{l}\text { ANoVA 1able }\\\begin{array} { r | r | r | r | r | r } \text { Source } & \text { DF } & \text { Sum squares } & \text { Mean square } & \text { F test } & \text { P-value } \\\hline \mathrm { A } & 2 & 415.87305 & 207.93652 & 1.88259 & .1637 \\\mathrm {~B} & 3 & 2997.47186 & 999.15729 & 9.04603 & .0001 \\\text { Interaction } & 6 & 707.26626 & 117.87771 & 1.06723 & .3958 \\\text { Error } & 46 & 5080.81667 & 110.45254 & & \\\text { Total } & 57 & 9201.42784 & & &\end{array}\end{array}
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