A. the x-variable
B. the independent variable
C. the predictor variable
D. all of the above (a-c) are correct
✅ The correct answer is option D.
Statistics MCQs
The coefficient of correlation____________
A. is the square of the coefficient of determination
B. is the square root of the coefficient of determination
C. is the same as r-square
D. can never be negative
✅ The correct answer is option B.
In a regression analysis if r 2 = 1, then ___________
A. SSE must also be equal to one
B. SSE must be equal to zero
C. SSE can be any positive value
D. SSE must be negative
✅ The correct answer is option B.
Larger values of r 2 (R2 ) imply that the observations are more closely grouped about the __________
A. average value of the independent variables
B. average value of the dependent variable
C. least squares line
D. origin
✅ The correct answer is option C.
In least squares regression, which of the following is not a required assumption about the error term ε? ___________
A. The expected value of the error term is one.
B. The variance of the error term is the same for all values of x.
C. The values of the error term are independent.
D. The error term is normally distributed)
✅ The correct answer is option A.
Regression analysis was applied to return rates of sparrowhawk colonies. Regression analysis was used to study the relationship between return rate (x: % of birds that return to the colony in a given year) and immigration rate (y: % of new adults that join the colony per year). The following regression equation was obtained) ! = 31.9 – 0.34x Based on the above estimated regression equation, if the return rate were to decrease by 10% the rate of immigration to the colony would________________
A. increase by 34%
B. increase by 3.4%
C. decrease by 0.34%
D. decrease by 3.4%
✅ The correct answer is option B.
In regression analysis, the variable that is being predicted is the __________
A. response, or dependent, variable
B. independent variable
C. intervening variable
D. is usually x
✅ The correct answer is option A.
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.
✅ The correct answer is option C.
SSE can never be _____________
A. larger than SST
B. smaller than SST
C. equal to 1
D. equal to zero
✅ The correct answer is option A.
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
✅ The correct answer is option C.