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= .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 11198 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 11199 Chapter 01  An Introduction to Business Statistics 3. A simple linear regression model is an equation that describes the straightline 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 11200 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 11201 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 11202 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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 Winter '14

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