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Unformatted text preview: he last year to use for the chisquare test of independence.
A. 23.0, 46.0
B. 27.8, 41.2
C. 189.5, 189.5
D. 34.5, 34.5 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 3
Topic: ChiSquare 11137 Chapter 01  An Introduction to Business Statistics 94. In a study of car accidents and drivers who use cell phones, the following sample data are
collected: At a significance level of 0.05, determine the appropriate degrees of freedom and the rejection
point condition for the test.
A. 1, 3.84
B. 4, 9.49
C. 2, 5.99
D. 3, 7.81
(r1) (c1) = 1 degree of freedom AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 3
Topic: ChiSquare 11138 Chapter 01  An Introduction to Business Statistics 95. In a study of car accidents and drivers who use cell phones, the following sample data are
collected: Calculate the chisquare statistic for this test of independence.
A. 3.84
B. 4.76
C. 1.50
D. 19.04 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 3
Topic: ChiSquare 11139 Chapter 01  An Introduction to Business Statistics 96. In a study of car accidents and drivers who use cell phones, the following sample data are
collected: Use a significance level of 0.05 and determine if the use of a cell phone and having an auto
accident are independent (null hypothesis is they are independent).
A. Reject H0
B. Fail to reject H0
Ho: Using a cell phone and having an accident are independent
Ha: Using a cell phone and having an accident are dependent
χ 2 = 1.5023, χ2.05,1 = 3.841
Reject Ho if χ2 > χ2.05,1 failed to reject Ho AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 3
Topic: ChiSquare Chapter 13
Simple Linear Regression Analysis
True / False Questions 1. The dependent variable is the variable that is being described, predicted, or controlled.
True False 2. The error term is the difference between an individual value of the dependent variable and
the corresponding mean value of the dependent variable.
True False 3. A simple linear regression model is an equation that describes the straightline relationship
between a dependent variable and an independent variable.
True False 11140 Chapter 01  An Introduction to Business Statistics 4. The residual is the difference between the observed value of the dependent variable and the
predicted value of the dependent variable.
True False 5. The experimental region is the range of the previously observed values of the dependent
variable.
True False 6. The simple coefficient of determination is the proportion of total variation explained by the
regression line.
True False 11141 Chapter 01  An Introduction to Business Statistics 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.
True False 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.
True False 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 False 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.
True False 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.
True False 12. If r = 1, then we can conclude that there is a perfect relationship between X and Y.
True False 13. The correlation coefficient is the ratio of explained variation to total variation.
True False 11142 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).
True False 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 False 16. The least squares simple linear regression line minimizes the sum of the vertical
deviations between the line and the data points.
True False 17. The notation
True False refers to the average value of the dependent variable Y. 18. A significant positive correlation between X and Y implies that changes in X cause Y to
change.
True False 19. The standard error of the estimate (standard error) is the estimated standard deviation of
the distribution of the independent variable (X) for all values of the dependent variable (Y).
True False 20. The estimated simple linear regression equation minimizes the sum of the squared
deviations between each value of Y and the line.
True False 11143 Chapter 01  An Introduction to Business Statistics
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 Winter '14

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