In a completely randomised design, 12 experimental units were assigned to the first treatment, 15 units to the second treatment, and 18 units to the third treatment. A partial ANOVA table is shown below: \[\begin{array} { | l | c | c | c | c | } \hline \text { Source of Variation } & \text { SS } & d f & M S & F \\ \hline \text { Treatments } & * & * & * & 9 \\ \hline \text { Error } & * & * & 35 & \\ \hline \text { Total } & * & * & & \\ \hline \end{array}\] Fill in the blanks (identified by asterisks) in the above ANOVA table.

The answer of In a completely randomised design, 12 experimental...

In single-factor analysis of variance, if large differences exist among the sample means, it is then reasonable to: \(\begin{array}{|l|l|} \hline A.&\text {reject the null hypothesis. }\\ \hline B.&\text {reject the alternative hypothesis. }\\ \hline C.&\text { fail to reject the null hypothesis.}\\ \hline D.&\text {None of these choices are correct. }\\ \hline \end{array}\)

The answer of In single-factor analysis of variance, if large...

Which of the following is the primary interest of designing a randomised block experiment? \(\begin{array}{|l|l|} \hline \text { A. } & \text { Reduce the variation among blocks. } \\ \hline \text { B. } & \begin{array}{l} \text { Reduce the within-treatments variation to more easily detect differences among the } \\ \text { treatment means. } \end{array} \\ \hline \text { C. } & \begin{array}{l} \text { Increase the between-treatments variation to more easily detect differences among the } \\ \text { treatment means. } \end{array} \\ \hline \text { D. } & \text { Increase the total sum of squares. } \\ \hline \end{array}\)

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

Exam 16: Analysis of Variance

In a completely randomised design, 12 experimental units were assigned to the first treatment, 15 units to the second treatment, and 18 units to the third treatment. A partial ANOVA table is shown below: Source of Variation SS df MS F Treatments * * * 9 Error * * 35 Total * * Fill in the blanks (identified by asterisks) in the above ANOVA table.

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Question 121

A survey is to be conducted to compare the superannuation contributions made by employees from three Victorian universities. Employees are to be randomly selected from each of the three universities and the dollar amounts of their contributions recorded. The ANOVA model most likely to fit this situation is the randomised block design.

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Question 122

In single-factor analysis of variance, if large differences exist among the sample means, it is then reasonable to: A. reject the null hypothesis. B. reject the alternative hypothesis. C. fail to reject the null hypothesis. D. None of these choices are correct.

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Question 123

The sum of squares for treatments, SST, achieves its smallest value (zero) when all the sample means are equal.

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Question 124

Which of the following is the primary interest of designing a randomised block experiment? A. Reduce the variation among blocks. B. Reduce the within-treatments variation to more easily detect differences among the treatment means. C. Increase the between-treatments variation to more easily detect differences among the treatment means. D. Increase the total sum of squares.

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Question 125

In single-factor analysis of variance, if large differences exist among the sample means, it is then reasonable to: A. reject the null hypothesis. B. reject the alternative hypothesis. C. fail to reject the null hypothesis. D. None of these choices are correct.

The sum of squares for treatments, SST, achieves its smallest value (zero) when all the sample means are equal.

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

Additional Tests for Nominal Data: Chi-Squared Tests

Simple Linear Regression and Correlation

Multiple Regression

Model Building

Nonparametric Techniques

Statistical Inference: Conclusion

Time-Series Analysis and Forecasting

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