Which of the following is the alternative hypothesis tested in applications of the Kruskal-Wallis test? $\begin{array}{|l|l|} \hline \text { A. } & \text {At least two population locations are the same. } \\ \hline \text { B. } & \text { The locations of all \( k $ populations differ.} \\ \hline \text { C. } & \text { At least two population locations differ.} \\ \hline \text { D. } & \text { The locations of all $ k $ populations are the same.} \\ \hline \end{array}\)

The answer of Which of the following is the alternative...

Which of the following best describes when a non-parametric test for comparing two or more populations should be used instead of its parametric counterpart? $\begin{array}{|l|l|} \hline A&\text {When the sample sizes are large. }\\ \hline B&\text {When the populations are normally distributed.}\\ \hline C&\text { When the data are ordinal (ranked) or numerical and non-normal.}\\ \hline D&\text {When the data are numerical. }\\ \hline \end{array}$

The answer of Which of the following best describes when...

A non-parametric method to compare two populations, when the samples are matched pairs and the data are ordinal, is the: $\begin{array}{|l|l|} \hline A&\text { Wil coxon signed rank sum test. }\\ \hline B&\text { sign test. }\\ \hline C&\text { Wil coxon rank sum test. }\\ \hline D&\text { matched pairs } t \text {-test. }\\ \hline \end{array}$

The answer of A non-parametric method to compare two populations,...

Which of the following best describes when to apply the Wilcoxon rank sum test to determine whether the location of population 1 is different from the location of population 2? $\begin{array}{|l|l|} \hline A&\text {The samples must be drawn from normal populations. }\\ \hline B&\text {The samples must be independent. }\\ \hline C&\text {The samples must be drawn from matched pairs experiment. }\\ \hline D&\text { The sample size must be larger than 30 .}\\ \hline \end{array}$

The answer of Which of the following best describes when...

A non-parametric method to compare two or more populations, when the samples are matched pairs and the data are either ordinal or interval but not normal, is the: $\begin{array}{|l|l|} \hline A&\text {Wilcoxon signed rank sum test. }\\ \hline B&\text { sign test.}\\ \hline C&\text { Friedman test.}\\ \hline D&\text {Kruskal-Wallis test. }\\ \hline \end{array}$

The answer of A non-parametric method to compare two or...

The non-parametric tests discussed in your textbook (Wilcoxon rank sum test, sign test, Wilcoxon signed rank sum test, Kruskal-Wallis test and Friedman test) all require that the probability distributions be: $\begin{array}{|l|l|} \hline A&\text {identical except with respect to location. }\\ \hline B&\text {identical except with respect to spread (variance). }\\ \hline C&\text {identical except with respect to shape (distribution). }\\ \hline D&\text { different with respect to location, spread, and shape.}\\ \hline \end{array}$

The answer of The non-parametric tests discussed in your textbook...

In a Kruskal-Wallis test there are five samples and the value of the test statistic is calculated as H = 11.15. The most accurate statement that can be made about the p-value is that: $\begin{array}{|l|l|} \hline \text { A. } & \text {it is smaller than 0.01 . } \\ \hline \text { B. } & \text { it is greater than 0.025 but smaller than 0.05 .} \\ \hline \text { C. } & \text { it is greater than 0.01 but smaller than 0.025 .} \\ \hline \text { D. } & \text { it is greater than 0.05 .} \\ \hline \end{array}$

The answer of In a Kruskal-Wallis test there are five...

In a normal approximation to the Wilcoxon signed rank sum test, the test statistic is calculated as z = 1.59. For a two-tail test, the p-value is: $\begin{array}{|l|l|} \hline\text { A. } & 0.3882 . \\ \hline \text { B. } & 0.0559 \\ \hline \text { C. } & 0.1118 . \\ \hline \text { D. } & 0.4441 \\ \hline \end{array}$

The answer of In a normal approximation to the Wilcoxon...

The following data represent the test scores of eight students on a statistics test before and after attending extra help sessions for the test. $\begin{array} { | l | c | c | } \hline \text { Student } & \text { Before } & \text { After } \\ \hline \text { Abby } & 82 & 90 \\ \hline \text { Brenda } & 75 & 86 \\ \hline \text { Carmen } & 90 & 90 \\ \hline \text { David } & 68 & 62 \\ \hline \text { Edward } & 87 & 89 \\ \hline \text { Frank } & 73 & 75 \\ \hline \text { Gill } & 81 & 78 \\ \hline \text { Heidi } & 92 & 98 \\ \hline \end{array}$ Uses the Wilcoxon signed rank sum test to determine at the 5% significance level whether the extra help sessions have been effective.

@#IMG-DLM& The two population locations are the sa

The Wilcoxon rank sum test (like most of the non-parametric tests presented in your textbook) actually tests to determine whether the population distributions have identical: $\begin{array}{|l|l|} \hline A&\text {locations. }\\ \hline B&\text {spreads (variances). }\\ \hline C&\text {shapes. }\\ \hline D&\text { All of the above are correct answers.}\\ \hline \end{array}$

The answer of The Wilcoxon rank sum test (like most...

Use the Wilcoxon rank sum test on the data below to determine at the 10% significance level whether the two population locations differ. $\begin{array} { | l | r | r | r | r | r | r | r | } \hline \text { Sample 1: } & 17 & 20 & 18 & 25 & 16 & 22 & \\ \hline \text { Sample 2: } & 17 & 25 & 33 & 38 & 15 & 26 & 21 \\ \hline \end{array}$

@#IMG-DLM& The two population locations

Exam 21: Nonparametric Techniques

Which of the following is the alternative hypothesis tested in applications of the Kruskal-Wallis test? A. At least two population locations are the same. B. The locations of all k populations differ. C. At least two population locations differ. D. The locations of all k populations are the same.

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Question 21

Which of the following best describes when a non-parametric test for comparing two or more populations should be used instead of its parametric counterpart? A When the sample sizes are large. B When the populations are normally distributed. C When the data are ordinal (ranked) or numerical and non-normal. D When the data are numerical.

(Short Answer)

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Question 22

A non-parametric method to compare two populations, when the samples are matched pairs and the data are ordinal, is the: A Wil coxon signed rank sum test. B sign test. C Wil coxon rank sum test. D matched pairs t -test.

(Short Answer)

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Question 23

In the sign test applications, the normal approximation to the binomial distribution may be used whenever the number of nonzero differences is greater than or equal to: A. 5 B. 20 C. 10 D. 30

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Question 24

Which of the following best describes when to apply the Wilcoxon rank sum test to determine whether the location of population 1 is different from the location of population 2? A The samples must be drawn from normal populations. B The samples must be independent. C The samples must be drawn from matched pairs experiment. D The sample size must be larger than 30 .

(Short Answer)

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Question 25

The Kruskal-Wallis test requires independent sample.

(True/False)

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Question 26

The following statistics are drawn from two independent samples: $T _ { A } = 800$ , $n _ { A } = 25$ , $T _ { B } = 1100$ , $n _ { B } = 28$ . Test at the 5% significance level to determine whether the two population locations differ.

(Essay)

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Question 27

A non-parametric method to compare two or more populations, when the samples are matched pairs and the data are either ordinal or interval but not normal, is the: A Wilcoxon signed rank sum test. B sign test. C Friedman test. D Kruskal-Wallis test.

(Short Answer)

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Question 28

The Friedman test is employed to compare two or more populations when the data are generated from a matched pairs experiment, and are either ordinal or interval but not normally distributed.

(True/False)

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Question 29

A Wilcoxon rank sum test for comparing two populations involves two independent samples of sizes 5 and 7. The alternative hypothesis is stated as: The location of population 1 is different from the location of population 2. The appropriate critical values at the 5% significance level are: A. 20,45 . B. 22,43 . C. 33,58 . D. 35,56 .

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Question 30

The non-parametric tests discussed in your textbook (Wilcoxon rank sum test, sign test, Wilcoxon signed rank sum test, Kruskal-Wallis test and Friedman test) all require that the probability distributions be: A identical except with respect to location. B identical except with respect to spread (variance). C identical except with respect to shape (distribution). D different with respect to location, spread, and shape.

(Short Answer)

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Question 31

The Wilcoxon rank sum test is used to compare two populations when the samples are independent and the data are either ordinal or interval but not normally distributed.

(True/False)

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Question 32

A Wilcoxon rank sum test for comparing two independent samples involves two samples of sizes 6 and 9. The alternative hypothesis is that the location of population 1 is to the left of the location of population 2. Using the 0.05 significance level, the appropriate critical values are 31 and 65.

(True/False)

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Question 33

In a Kruskal-Wallis test there are five samples and the value of the test statistic is calculated as H = 11.15. The most accurate statement that can be made about the p-value is that: A. it is smaller than 0.01 . B. it is greater than 0.025 but smaller than 0.05 . C. it is greater than 0.01 but smaller than 0.025 . D. it is greater than 0.05 .

(Short Answer)

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Question 34

In a normal approximation to the Wilcoxon signed rank sum test, the test statistic is calculated as z = 1.59. For a two-tail test, the p-value is: A. 0.3882. B. 0.0559 C. 0.1118. D. 0.4441

(Short Answer)

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Question 35

The following data represent the test scores of eight students on a statistics test before and after attending extra help sessions for the test. Student Before After Abby 82 90 Brenda 75 86 Carmen 90 90 David 68 62 Edward 87 89 Frank 73 75 Gill 81 78 Heidi 92 98 Uses the Wilcoxon signed rank sum test to determine at the 5% significance level whether the extra help sessions have been effective.

(Essay)

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Question 36

A matched pairs experiment yielded the following results: Number of positive differences = 18, number of negative differences = 7, number of zero differences = 3. Can we infer at the 5% significance level that the location of population 1 is to the right of the location of population 2?

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Question 37

In a normal approximation to the sign test, the standardised test statistic is calculated as z = 2.07. If the alternative hypothesis states that the location of population 1 is to the right of the location of population 2, then the p-value of the test is 0.0192.

(True/False)

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Question 38

The Wilcoxon rank sum test (like most of the non-parametric tests presented in your textbook) actually tests to determine whether the population distributions have identical: A locations. B spreads (variances). C shapes. D All of the above are correct answers.

(Short Answer)

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Question 39

Use the Wilcoxon rank sum test on the data below to determine at the 10% significance level whether the two population locations differ. Sample 1: 17 20 18 25 16 22 Sample 2: 17 25 33 38 15 26 21

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Question 40

Which of the following is the alternative hypothesis tested in applications of the Kruskal-Wallis test? A. At least two population locations are the same. B. The locations of all k populations differ. C. At least two population locations differ. D. The locations of all k populations are the same.

A non-parametric method to compare two populations, when the samples are matched pairs and the data are ordinal, is the: A Wil coxon signed rank sum test. B sign test. C Wil coxon rank sum test. D matched pairs t -test.

In the sign test applications, the normal approximation to the binomial distribution may be used whenever the number of nonzero differences is greater than or equal to: A. 5 B. 20 C. 10 D. 30

The Kruskal-Wallis test requires independent sample.

The following statistics are drawn from two independent samples: $T _ { A } = 800$ , $n _ { A } = 25$ , $T _ { B } = 1100$ , $n _ { B } = 28$ . Test at the 5% significance level to determine whether the two population locations differ.

A non-parametric method to compare two or more populations, when the samples are matched pairs and the data are either ordinal or interval but not normal, is the: A Wilcoxon signed rank sum test. B sign test. C Friedman test. D Kruskal-Wallis test.

The Friedman test is employed to compare two or more populations when the data are generated from a matched pairs experiment, and are either ordinal or interval but not normally distributed.

The Wilcoxon rank sum test is used to compare two populations when the samples are independent and the data are either ordinal or interval but not normally distributed.

A Wilcoxon rank sum test for comparing two independent samples involves two samples of sizes 6 and 9. The alternative hypothesis is that the location of population 1 is to the left of the location of population 2. Using the 0.05 significance level, the appropriate critical values are 31 and 65.

In a normal approximation to the Wilcoxon signed rank sum test, the test statistic is calculated as z = 1.59. For a two-tail test, the p-value is: A. 0.3882. B. 0.0559 C. 0.1118. D. 0.4441

A matched pairs experiment yielded the following results: Number of positive differences = 18, number of negative differences = 7, number of zero differences = 3. Can we infer at the 5% significance level that the location of population 1 is to the right of the location of population 2?

In a normal approximation to the sign test, the standardised test statistic is calculated as z = 2.07. If the alternative hypothesis states that the location of population 1 is to the right of the location of population 2, then the p-value of the test is 0.0192.

The Wilcoxon rank sum test (like most of the non-parametric tests presented in your textbook) actually tests to determine whether the population distributions have identical: A locations. B spreads (variances). C shapes. D All of the above are correct answers.

Use the Wilcoxon rank sum test on the data below to determine at the 10% significance level whether the two population locations differ. Sample 1: 17 20 18 25 16 22 Sample 2: 17 25 33 38 15 26 21

What Is Statistics

Types of Data, Data Collection and Sampling

Graphical Descriptive Methods Nominal Data

Graphical Descriptive Techniques Numerical Data

Numerical Descriptive Measures

Probability

Random Variables and Discrete Probability Distributions

Continuous Probability Distributions

Statistical Inference: Introduction

Sampling Distributions

Estimation: Describing a Single Population

Estimation: Comparing Two Populations

Hypothesis Testing: Describing a Single Population

Hypothesis Testing: Comparing Two Populations

Inference About Population Variances

Analysis of Variance

Additional Tests for Nominal Data: Chi-Squared Tests

Simple Linear Regression and Correlation

Multiple Regression

Model Building

Statistical Inference: Conclusion

Time-Series Analysis and Forecasting

Index Numbers

Decision Analysis

Filters

Exam 21: Nonparametric Techniques

Which of the following is the alternative hypothesis tested in applications of the Kruskal-Wallis test? A. At least two population locations are the same. B. The locations of all k populations differ. C. At least two population locations differ. D. The locations of all k populations are the same.

A non-parametric method to compare two populations, when the samples are matched pairs and the data are ordinal, is the: A Wil coxon signed rank sum test. B sign test. C Wil coxon rank sum test. D matched pairs t -test.

In the sign test applications, the normal approximation to the binomial distribution may be used whenever the number of nonzero differences is greater than or equal to: A. 5 B. 20 C. 10 D. 30

The Kruskal-Wallis test requires independent sample.

The following statistics are drawn from two independent samples: TA=800T _ { A } = 800TA​=800 , nA=25n _ { A } = 25nA​=25 , TB=1100T _ { B } = 1100TB​=1100 , nB=28n _ { B } = 28nB​=28 . Test at the 5% significance level to determine whether the two population locations differ.

A non-parametric method to compare two or more populations, when the samples are matched pairs and the data are either ordinal or interval but not normal, is the: A Wilcoxon signed rank sum test. B sign test. C Friedman test. D Kruskal-Wallis test.

The Friedman test is employed to compare two or more populations when the data are generated from a matched pairs experiment, and are either ordinal or interval but not normally distributed.

The Wilcoxon rank sum test is used to compare two populations when the samples are independent and the data are either ordinal or interval but not normally distributed.

A Wilcoxon rank sum test for comparing two independent samples involves two samples of sizes 6 and 9. The alternative hypothesis is that the location of population 1 is to the left of the location of population 2. Using the 0.05 significance level, the appropriate critical values are 31 and 65.

In a normal approximation to the Wilcoxon signed rank sum test, the test statistic is calculated as z = 1.59. For a two-tail test, the p-value is: A. 0.3882. B. 0.0559 C. 0.1118. D. 0.4441

A matched pairs experiment yielded the following results: Number of positive differences = 18, number of negative differences = 7, number of zero differences = 3. Can we infer at the 5% significance level that the location of population 1 is to the right of the location of population 2?

In a normal approximation to the sign test, the standardised test statistic is calculated as z = 2.07. If the alternative hypothesis states that the location of population 1 is to the right of the location of population 2, then the p-value of the test is 0.0192.

The Wilcoxon rank sum test (like most of the non-parametric tests presented in your textbook) actually tests to determine whether the population distributions have identical: A locations. B spreads (variances). C shapes. D All of the above are correct answers.

Use the Wilcoxon rank sum test on the data below to determine at the 10% significance level whether the two population locations differ. Sample 1: 17 20 18 25 16 22 Sample 2: 17 25 33 38 15 26 21

What Is Statistics

Types of Data, Data Collection and Sampling

Graphical Descriptive Methods Nominal Data

Graphical Descriptive Techniques Numerical Data

Numerical Descriptive Measures

Probability

Random Variables and Discrete Probability Distributions

Continuous Probability Distributions

Statistical Inference: Introduction

Sampling Distributions

Estimation: Describing a Single Population

Estimation: Comparing Two Populations

Hypothesis Testing: Describing a Single Population

Hypothesis Testing: Comparing Two Populations

Inference About Population Variances

Analysis of Variance

Additional Tests for Nominal Data: Chi-Squared Tests

Simple Linear Regression and Correlation

Multiple Regression

Model Building

Statistical Inference: Conclusion

Time-Series Analysis and Forecasting

Index Numbers

Decision Analysis

Filters

The following statistics are drawn from two independent samples: $T _ { A } = 800$ , $n _ { A } = 25$ , $T _ { B } = 1100$ , $n _ { B } = 28$ . Test at the 5% significance level to determine whether the two population locations differ.