UCF QMB 3200 FINAL EXAM TEST
STUDY
QUESTIONS AND ANSWERS (VERIFIED ANSWERS)
1. The difference between the observed value of the dependent variable and
the value predicted using the estimated regression equation is called a(n)
ANS residual
2. Influential observations always
ANS increase the value of the correlation.
3. 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
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,ANS normal probability plot.
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, 4. The tests of significance in regression analysis are based on several as-
sumptions about the error term [. 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
ANS linear
5. Suppose a residual plot of x verses the residuals, y - w, shows a nonconstant
variance. In particular, as the values of x increase, suppose that the values of the
residuals also increase. This means that
ANS as the values of x get larger, the ability to predict y becomes less accurate.
6. In a regression analysis, an outlier will always increase
ANS the value of thecorrelation.
7. Regression analysis can be interpreted as a procedure for establishing a
cause-and-effect relationship between variables
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STUDY
QUESTIONS AND ANSWERS (VERIFIED ANSWERS)
1. The difference between the observed value of the dependent variable and
the value predicted using the estimated regression equation is called a(n)
ANS residual
2. Influential observations always
ANS increase the value of the correlation.
3. 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
1/6
,ANS normal probability plot.
2/6
, 4. The tests of significance in regression analysis are based on several as-
sumptions about the error term [. 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
ANS linear
5. Suppose a residual plot of x verses the residuals, y - w, shows a nonconstant
variance. In particular, as the values of x increase, suppose that the values of the
residuals also increase. This means that
ANS as the values of x get larger, the ability to predict y becomes less accurate.
6. In a regression analysis, an outlier will always increase
ANS the value of thecorrelation.
7. Regression analysis can be interpreted as a procedure for establishing a
cause-and-effect relationship between variables
3/6
