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Unformatted text preview: ≠ 0 by setting = .01. Show the test statistic used in the decision. A. -5.908, reject the null hypothesis B. 5.908, reject the null hypothesis C. 9.35, reject the null hypothesis D. -2.977, reject the null hypothesis 1-1198 Chapter 01 - An Introduction to Business Statistics Chapter 13 Simple Linear Regression Analysis Answer Key True / False Questions 1. The dependent variable is the variable that is being described, predicted, or controlled. TRUE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 1 Topic: Simple Linear Regression 2. The error term is the difference between an individual value of the dependent variable and the corresponding mean value of the dependent variable. FALSE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 1 Topic: Simple Linear Regression 1-1199 Chapter 01 - An Introduction to Business Statistics 3. A simple linear regression model is an equation that describes the straight-line relationship between a dependent variable and an independent variable. TRUE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 1 Topic: 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 AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 1 Topic: Simple Linear Regression 5. The experimental region is the range of the previously observed values of the dependent variable. FALSE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 1 Topic: Simple Linear Regression 1-1200 Chapter 01 - An Introduction to Business Statistics 6. The simple coefficient of determination is the proportion of total variation explained by the regression line. TRUE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 6 Topic: Coefficient of determination 7. When using simple regression analysis, if there is a strong 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 AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Hard Learning Objective: 6 Topic: Correlation 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 AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 9 Topic: Residual analysis 9. In simple regression analysis, r2 is a percentage measure and measures the proportion of the variation explained by the simple linear regression model. TRUE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 6 Topic: Coefficient of determination 1-1201 Chapter 01 - An Introduction to Business Statistics 10. In a simple linear regression model, the coefficient of determination not only indicates the strength of the relationship between independent and dependent variable, but also shows whether the relationship is positive or negative. FALSE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 6 Topic: Coefficient of determination 11. In simple linear regression analysis, if the error terms exhibit a positive or negative autocorrelation over time, then the assumption of constant variance is violated. FALSE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 9 Topic: Residual analysis 12. If r = -1, then we can conclude that there is a perfect relationship between X and Y. TRUE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 6 Topic: Correlation 13. The correlation coefficient is the ratio of explained variation to total variation. FALSE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Easy Learning Objective: 6 Topic: Correlation 1-1202 Chapter 01 - An Introduction to Business Statistics 14. In simple linear regression analysis, we assume that the variance of the independent variable (X) is equal to the variance of the dependent variable (Y). FALSE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Easy Learning Objective: 3 Topic: Simple Linear Regression model assumptions 15. The slope of the simple linear regression equation represents the average change in the value of the dependent variable per unit change in the independent variable (X). TRUE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Easy Learning Objective: 1 Topic: Simple Linear Regression 16. The least squares simple linear regression line minimizes the sum of the vertical deviations between the line and the data points. FALSE AACSB: Reflective Thinking Bloom's: Knowledge Difficulty: Medium Learning Objective: 2 Topic: Simple Linear Regression 17. The notation FALSE refers to the average value of the dependent variable Y. AACSB: Reflective Thi...
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