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Business Statistics In Practice 8th Edition By Bowerman – Test Bank

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Business Statistics In Practice 8th Edition By Bowerman – Test Bank

Chapter 11 Test Bank – Static KEY

1. If factors being studied cannot be controlled, the data are said to be observational.
TRUE
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
Blooms: Understand
Difficulty: 1 Easy
Learning Objective: 11-01 Explain the basic terminology and concepts of experimental design.
Topic: Basic Concepts of Experimental Design

2. 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
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
Blooms: Understand
Difficulty: 2 Medium
Learning Objective: 11-02 Compare several different population means by using a one-way analysis of variance.
Topic: One-Way Analysis of Variance

3. In a completely randomized (one-way) ANOVA, with other things being equal, as the sample means get closer to each other, the probability of rejecting the null hypothesis decreases.

TRUE
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
Blooms: Understand
Difficulty: 2 Medium
Learning Objective: 11-02 Compare several different population means by using a one-way analysis of variance.
Topic: One-Way Analysis of Variance

4. The experimentwise α for the 95 percent individual confidence interval for μ1 − μ2 (treatment mean 1 − treatment mean 2) will always be smaller than the experimentwise α for a Tukey 95 percent simultaneous confidence interval for μ1 − μ2.

FALSE
Tukey’s formula yields the most precise (smallest) simultaneous confidence intervals.
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
Blooms: Understand
Difficulty: 2 Medium
Learning Objective: 11-02 Compare several different population means by using a one-way analysis of variance.
Topic: One-Way Analysis of Variance

5. When using a randomized block design, the interaction effect between the block and treatment factors cannot be separated from the error term.
TRUE
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
Blooms: Understand
Difficulty: 3 Hard
Learning Objective: 11-03 Compare treatment effects and block effects by using a randomized block design.
Topic: The Randomized Block Design

6. Experimental data are collected so that the values of the dependent variables are set before the values of the independent variable are observed.

FALSE
Values of the independent variables are observed before collecting the dependent variables.
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
Blooms: Understand
Difficulty: 2 Medium
Learning Objective: 11-01 Explain the basic terminology and concepts of experimental design.
Topic: Basic Concepts of Experimental Design

7. The 95 percent individual confidence interval for μ1 − μ2 (treatment mean 1 − treatment mean 2) will always be smaller than the Tukey 95 percent simultaneous confidence interval for μ1 − μ2.
TRUE
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
Blooms: Understand
Difficulty: 2 Medium
Learning Objective: 11-02 Compare several different population means by using a one-way analysis of variance.
Topic: One-Way Analysis of Variance

8. After rejecting the null hypothesis of equal treatments, a researcher decided to compute a 95 percent confidence interval for the difference between the mean of treatment 1 and mean of treatment 2 based on the Tukey procedure. At α = .05, if the confidence interval includes the value of zero, then we can reject the hypothesis that the two population means are equal.
FALSE
When a confidence interval contains zero, the null hypothesis that the means are equal cannot be rejected.
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
Blooms: Understand
Difficulty: 3 Hard
Learning Objective: 11-02 Compare several different population means by using a one-way analysis of variance.
Topic: One-Way Analysis of Variance

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

FALSE
The treatment sum of squares measures the between-treatment variability.
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
Blooms: Understand
Difficulty: 2 Medium
Learning Objective: 11-02 Compare several different population means by using a one-way analysis of variance.
Topic: One-Way Analysis of Variance

10. In one-way ANOVA, a large value of F results when the within-treatment variability is large compared to the between-treatment variability.
FALSE
F is the MST/MSE, so F is large with a larger between-treatment variability.
AACSB: Reflective Thinking
Accessibility: Keyboard Navigation
Blooms: Understand
Difficulty: 2 Medium
Learning Objective: 11-02 Compare several different population means by using a one-way analysis of variance.
Topic: One-Way Analysis of Variance

11. In one-way ANOVA, the numerator degrees of freedom equals the number of samples being compared.
FALSE
Numerator degrees of freedom = number of treatments − 1

 

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