Business Statistics In Practice, 3rd Canadian Edition By Bruce – Test Bank

c11 Key

1. The dependent variable is the variable that is being described, predicted, or controlled.
TRUE

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Bowerman – Chapter 11 #1
Difficulty: Medium
Learning Objective: 11-02 Calculate the correlation coefficient statistic

2. The error term in a simple linear regression model is the difference between an individual value of the dependent variable and the corresponding mean value of the dependent variable.
FALSE

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Bowerman – Chapter 11 #2
Difficulty: Medium
Learning Objective: 11-04 Define what is meant by simple linear regression

3. A simple linear regression model is an equation that describes the straight-line relationship between a dependent variable and an independent variable.
TRUE

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Bowerman – Chapter 11 #3
Difficulty: Medium
Learning Objective: 11-04 Define what is meant by simple linear regression

4. The residual is the difference between the observed value of the dependent variable and the predicted value of the dependent variable.
TRUE

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Bowerman – Chapter 11 #4
Difficulty: Medium
Learning Objective: 11-06 Explain the meaning of each term in the linear regression equation

5. The experimental region is the range of the previously observed values of the dependent variable.
FALSE

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Bowerman – Chapter 11 #5
Difficulty: Medium
Learning Objective: 11-06 Explain the meaning of each term in the linear regression equation

6. The coefficient of determination is the proportion of total variation explained by the regression line.
TRUE

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Bowerman – Chapter 11 #6
Difficulty: Medium
Learning Objective: 11-03 Explain the resulting value of computing r2 (eta2) from a correlation

7. When using simple regression analysis, if there is a strong positive correlation between the independent and dependent variable, then we can conclude that an increase in the value of the independent variable causes an increase in the value of the dependent variable.
FALSE

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Bowerman – Chapter 11 #7
Difficulty: Hard
Learning Objective: 11-01 Describe the two properties of the correlation coefficient statistic

8. When there is positive autocorrelation, over time, negative error terms are followed by positive error terms and positive error terms are followed by negative error terms.
FALSE

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Bowerman – Chapter 11 #8
Difficulty: Medium
Learning Objective: 11-05 List the assumptions behind linear regression

9. In simple regression analysis, r2measures the proportion of the variation in the dependent variable explained by the simple linear regression model.
TRUE

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Bowerman – Chapter 11 #9
Difficulty: Medium
Learning Objective: 11-03 Explain the resulting value of computing r2 (eta2) from a correlation

10. In a simple linear regression model, the coefficient of determination indicates the strength and direction of the relationship between independent and dependent variable.
FALSE

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Bowerman – Chapter 11 #10
Difficulty: Medium
Learning Objective: 11-03 Explain the resulting value of computing r2 (eta2) from a correlation

11. In simple regression analysis, the quantity is called the total variation.
TRUE