Exam 11: Statistical Inferences for Population Variances

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If the total sum of squares in a one-way analysis of variance is 25 and the treatment sum of squares is 17,then what is the error sum of squares?

(Essay)

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Question 41

In one-way ANOVA,as the between-treatment variation decreases,the probability of rejecting the null hypothesis increases.

(True/False)

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Question 42

Different levels of a factor are called ____________.

(Multiple Choice)

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Question 43

Which one of the following is not an assumption of one-way analysis of variance?

(Multiple Choice)

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Question 44

If sample mean plots look essentially parallel,we can intuitively conclude that there is an interaction between the two factors.

(True/False)

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Question 45

In one-way ANOVA,a large value of F results when the within-treatment variability is large compared to the between-treatment variability.

(True/False)

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Question 46

In one-way ANOVA,other factors being equal,the further apart the treatment means are from each other,the more likely we are to reject the null hypothesis associated with the ANOVA F test.

(True/False)

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Question 47

In one-way ANOVA,the numerator degrees of freedom equals the number of samples being compared.

(True/False)

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Question 48

The error sum of squares measures the between-treatment variability.

(True/False)

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Question 49

The ___________________ units are the entities (objects,people,etc. )to which the treatments are assigned.

(Multiple Choice)

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Question 50

We have just performed a one-way ANOVA on a given set of data and rejected the null hypothesis for the ANOVA F test.Assume that we are able to perform a randomized block design ANOVA on the same data.For the randomized block design ANOVA,the null hypothesis for equal treatments will __________ be rejected.

(Multiple Choice)

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Question 51

When using a randomized block design,the interaction effect between the block and treatment factors cannot be separated from the error term.

(True/False)

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Question 52

In general,a Tukey simultaneous 100(1 − α)percent confidence interval is _________ the corresponding individual 100(1 − α)percent confidence interval.

(Multiple Choice)

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Question 53

A one-way analysis of variance is a method that allows us to estimate and compare the effects of several treatments on a response variable.

(True/False)

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Question 54

Showing 41 - 54 of 54

If the total sum of squares in a one-way analysis of variance is 25 and the treatment sum of squares is 17,then what is the error sum of squares?

In one-way ANOVA,as the between-treatment variation decreases,the probability of rejecting the null hypothesis increases.

Different levels of a factor are called ____________.

Which one of the following is not an assumption of one-way analysis of variance?

If sample mean plots look essentially parallel,we can intuitively conclude that there is an interaction between the two factors.

In one-way ANOVA,a large value of F results when the within-treatment variability is large compared to the between-treatment variability.

In one-way ANOVA,other factors being equal,the further apart the treatment means are from each other,the more likely we are to reject the null hypothesis associated with the ANOVA F test.

In one-way ANOVA,the numerator degrees of freedom equals the number of samples being compared.

The error sum of squares measures the between-treatment variability.

The ___________________ units are the entities (objects,people,etc. )to which the treatments are assigned.

When using a randomized block design,the interaction effect between the block and treatment factors cannot be separated from the error term.

In general,a Tukey simultaneous 100(1 − α)percent confidence interval is _________ the corresponding individual 100(1 − α)percent confidence interval.

A one-way analysis of variance is a method that allows us to estimate and compare the effects of several treatments on a response variable.

An Introduction to Business Statistics

Descriptive Statistics: Tabular and Graphical Methods

Descriptive Statistics: Numerical Methods

Probability

Discrete Random Variables

Continuous Random Variables

Sampling and Sampling Distributions

Confidence Intervals

Hypothesis Testing

Statistical Inferences for Means and Proportions

Experimental Design and Analysis of Variance

Chi-Square Tests

Simple Linear Regression Analysis

Multiple Regression and Model Building

Time Series Forecasting and Index Numbers

Nonparametric Methods

Decision Theory

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