Corelation and Regression
When a multiple correlation coefficient R 1.23 =1 , then R 2.13 is:
1
-1
0
None of these
1
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Regression modeling is a statistical framework for developing a mathematical equation that describes how :A. one explanatory and one or more response variables are related
B. several explanatory and several response variables response are related
C. one response and one or more explanatory variables are related
D. All of these are correct.
Which of the following is not cause of the correlation?
A. Direct relationship
B. Correlation due to any other common cause
C. Mutual Reaction
D. None of these
In a regression analysis if SSE = 200 and SSR = 300, then the coefficient of determination is :
A. 0.6667
B. 0.6000
C. 0.4000
D. 1.5000
When the correlation coefficient between x and y is positive, then as variable x decreases, variable yRemains the same:
A. Increases
B. Decreases
C. Changes linearly
D. none
The relationship between number of beers consumed (x) and blood alcohol content (y) was studied in 16 male college students by using least squares regression. The following regression equation was obtained from this study: != -0.0127 + 0.0180x The above equation implies that:
A. each beer consumed increases blood alcohol by 1.27%
B. on average it takes 1.8 beers to increase blood alcohol content by 1%
C. each beer consumed increases blood alcohol by an average of amount of 1.8%
D. each beer consumed increases blood alcohol by exactly 0.018
In regression, the equation that describes how the response variable (y) is related to the explanatoryvariable (x) is:
A. the correlation model
B. the regression model
C. used to compute the correlation coefficient
D. None of these alternatives is correct.
Which of the following is true if the estimating equation has to be a perfect estimator of the dependentvariable?
A. The coefficient of determination is -1
B. All the data points are on the regression line.
C. The standard error of the estimate is zero
D. B and C
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