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A sales manager for an advertising agency believes there is a relationship between the number of contacts and the amount of the sales. To verify this belief, the following data was collected:
What is the dependent variable?
A) Salesperson
B) Number of contacts
C) Amount of sales
D) All the above
What is the independent variable?
A) Salesperson
B) Number of contacts
C) Amount of sales
D) All the above
What is the Y-intercept of the linear equation?
A) –12.201
B) 2.1946
C) –2.1946
D) 12.201
What is the slope of the linear equation?
A) –12.201
B) 12.201
C) 2.1946
D) –2.1946
What is the value of the standard error of estimate?
A) 9.310
B) 8.778
C) 8.328
D) 86.68
What is the value of the coefficient of correlation?
A) 0.6317
B) 0.9754
C) 0.9513
D) 9.3104
What is the value of the coefficient of determination?
A) 9.3104
B) 0.9754
C) 0.6319
D) 0.9513
The 95% confidence interval for 30 calls is
A) 55.8, 51.5
B) 51.4, 55.9
C) 46.7, 60.56
D) 31.1, 76.2
The 95% prediction interval for a particular person making 30 calls is
A) 55.8, 51.5
B) 51.4, 55.9
C) 46.7, 60.6
D) 31.07, 76.19
What is the regression equation?
A) Y' = 2.1946 – 12.201X
B) Y' = –12.201 + 2.1946X
C) Y' = 12.201 + 2.1946X
D) Y' = 2.1946 + 12.201X
A valid multiple regression analysis assumes or requires that
A) The dependent variable is measured using an ordinal, interval, or ratio scale
B) The residuals follow an F-distribution
C) The independent variables and the dependent variable have a linear relationship
D) The observations are autocorrelated
How is the degree of association between a set of independent variables and a dependent variable measured?
A) Confidence intervals.
B) Autocorrelation
C) Coefficient of multiple determination
D) Standard error of estimate
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