QMB 3200 EXPECTED QUESTIONS
AND ANSWERS FOR EXAM 3
If a residual plot of x versus the residuals, y - ŷ, shows a non-
linear pattern, then we should conclude that:
A. the regression model was not based upon a large enough
sample size.
B. the regression model is useful for making predictions.
C. the regression model is not an adequate representation of
the relationship between the variables.
D. the regression model describes the relationship between x
and y very well.
the regression model is not an adequate representation of the
relationship between the variables.
In a regression analysis, an outlier will always increase:
A. the slope of the regression line.
B. the y-intercept.
C. the ability to predict y with precision.
D. the value of the correlation.
the ability to predict y with precision.
In a regression analysis, the error term ε is a random variable
with a mean or expected value of
A. zero.
B. one.
,C. any positive value.
D. any value.
Zero
In regression analysis, the variable that is being predicted is
the:
A. dependent variable.
B. confounding variable.
C. random variable.
D. independent variable.
Dependent Variable
The tests of significance in regression analysis are based on
assumptions about the error term ɛ . One such assumption is
that the variance of ɛ, denoted by 𝝈2, is:
A. greater as x increases.
B. the same for all values of x.
C. unrelated to the value of x.
D. less as x increases.
the same for all values of x
Influential observations always:
A. increase the value of the slope.
B. increase the value of the correlation.
C. increase the value of the y-intercept.
D. None of the above are correct.
increase the value of the correlation.
,The tests of significance in regression analysis are based on
assumptions about the error term ɛ. One such assumption is
that the error term follows ɛ a(n) _____ distribution for all
values of x.
A. binomial
B. normal
C. uniform
D. exponential
normal
The tests of significance in regression analysis are based on
several assumptions about the error term ɛ. Additionally, we
make an assumption about the form of the relationship
between x and y. We assume that the relationship between x
and y is:
A. constant.
B. linear.
C. quadratic.
D. exponential.
linear
An F test, based on the F probability distribution, can be used
to test for:
A. equality of the means of two populations.
B. significance in the relationship between two categorical
variables.
C. significance in regression
D. equality of two population proportions.
, significance in regression
The tests of significance in regression analysis are based on
assumptions about the error term ɛ. One such assumption is
that the error term ɛ is a random variable with a mean or
expected value of:
A. 0.
B. ŷ
C. x̄
D. 1.
0
Observations with extreme values for the independent
variables are called:
A. outliers.
B. influential observations.
C. high leverage points.
D. mistakes.
high leverage points.
A graph of the standardized residuals plotted against values of
the normal scores that helps to determine whether the
assumption that the error term has a normal probability
distribution appears to be valid is called a:
A. scatter diagram.
B. regression plot.
C. normal probability plot.
D. residual plot.
AND ANSWERS FOR EXAM 3
If a residual plot of x versus the residuals, y - ŷ, shows a non-
linear pattern, then we should conclude that:
A. the regression model was not based upon a large enough
sample size.
B. the regression model is useful for making predictions.
C. the regression model is not an adequate representation of
the relationship between the variables.
D. the regression model describes the relationship between x
and y very well.
the regression model is not an adequate representation of the
relationship between the variables.
In a regression analysis, an outlier will always increase:
A. the slope of the regression line.
B. the y-intercept.
C. the ability to predict y with precision.
D. the value of the correlation.
the ability to predict y with precision.
In a regression analysis, the error term ε is a random variable
with a mean or expected value of
A. zero.
B. one.
,C. any positive value.
D. any value.
Zero
In regression analysis, the variable that is being predicted is
the:
A. dependent variable.
B. confounding variable.
C. random variable.
D. independent variable.
Dependent Variable
The tests of significance in regression analysis are based on
assumptions about the error term ɛ . One such assumption is
that the variance of ɛ, denoted by 𝝈2, is:
A. greater as x increases.
B. the same for all values of x.
C. unrelated to the value of x.
D. less as x increases.
the same for all values of x
Influential observations always:
A. increase the value of the slope.
B. increase the value of the correlation.
C. increase the value of the y-intercept.
D. None of the above are correct.
increase the value of the correlation.
,The tests of significance in regression analysis are based on
assumptions about the error term ɛ. One such assumption is
that the error term follows ɛ a(n) _____ distribution for all
values of x.
A. binomial
B. normal
C. uniform
D. exponential
normal
The tests of significance in regression analysis are based on
several assumptions about the error term ɛ. Additionally, we
make an assumption about the form of the relationship
between x and y. We assume that the relationship between x
and y is:
A. constant.
B. linear.
C. quadratic.
D. exponential.
linear
An F test, based on the F probability distribution, can be used
to test for:
A. equality of the means of two populations.
B. significance in the relationship between two categorical
variables.
C. significance in regression
D. equality of two population proportions.
, significance in regression
The tests of significance in regression analysis are based on
assumptions about the error term ɛ. One such assumption is
that the error term ɛ is a random variable with a mean or
expected value of:
A. 0.
B. ŷ
C. x̄
D. 1.
0
Observations with extreme values for the independent
variables are called:
A. outliers.
B. influential observations.
C. high leverage points.
D. mistakes.
high leverage points.
A graph of the standardized residuals plotted against values of
the normal scores that helps to determine whether the
assumption that the error term has a normal probability
distribution appears to be valid is called a:
A. scatter diagram.
B. regression plot.
C. normal probability plot.
D. residual plot.
