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

Solutions Manual For Business Data In Observation, Third Canadian Edition By Bruce

• ISBN-10 ‏ : ‎ 0071339604
• ISBN-13 ‏ : ‎ 978-0071339605

Chapter 11 Key

1. The reliant variable is the factor that’s under scrutiny, anticipated, or controlled.
REAL

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Bowerman – Chapter 11 #1
Issue: Average
Study Objective: 11-02 Compute the correlation coefficient figure

2. The deviation period in a simple linear regression model is the gap between an individual value of the reliant variable and the corresponding average of the reliant variable.
FALSE

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Bowerman – Chapter 11 #2
Issue: Average
Study Objective: 11-04 Define what is implied by simple linear regression

3. A straightforward linear regression model is a formula that illustrates the direct connection between a reliant variable and an independent variable.
REAL

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Bowerman – Chapter 11 #3
Issue: Average
Study Objective: 11-04 Define what is implied by simple linear regression

4. The leftover is the disparity between the noticed value of the reliant variable and the predicted value of the reliant variable.
REAL

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Bowerman – Chapter 11 #4
Issue: Average
Study Objective: 11-06 Explain the meaning of each term in the linear regression equation

5. The experimental space is not the scope of the formerly observed values of the reliant variable.
FALSE

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Bowerman – Chapter 11 #5
Issue: Average
Study Objective: 11-06 Explain the meaning of each term in the linear regression equation

6. The determination coefficient is the percentage of overall variation clarified by the regression line.
REAL

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Bowerman – Chapter 11 #6
Issue: Average
Study Objective: 11-03 Explain the resulting value of computing r2 (eta2) from a correlation

7. If there is a strong affirmative correlation between the independent and reliant variable when using simple regression analysis, then it can be concluded that an increase in the value of the independent variable leads to an increase in the value of the reliant variable.
FALSE

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Bowerman – Chapter 11 #7
Issue: Difficult
Study Objective: 11-01 Describe the two properties of the correlation coefficient figure

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

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Bowerman – Chapter 11 #8
Issue: Average
Study Objective: 11-05 Enumerate the presumptions behind linear regression

9. In simple regression analysis, r2 measures the percentage of the variation in the reliant variable explained by the simple linear regression model.
REAL

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Bowerman – Chapter 11 #9
Issue: Average
Study Objective: 11-03 Explain the resulting value of computing r2 (eta2) from a correlation

10. In a simple linear regression model, the determination coefficient signifies the strength and direction of the relationship between independent and reliant variables.
FALSE

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Bowerman – Chapter 11 #10
Issue: Average
Study Objective: 11-03 Explain the resulting value of computing r2 (eta2) from a correlation

11. In simple regression analysis, this quantity is termed the total variation.
REAL