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EXAM TWO
BUS 310
A
NAME
A few scenarios follow which require you to choose an appropriate term. To refresh
your memory some of the terms that you have used include:
A. Intercept
B. Slope
C. Predicted Y
D. VIF
E. Scatter Diagram
F. Correlation
G. RSquared
H. Adjusted RSquared
I.
Standard Error
J.
Pvalues
K. Aptness of Fit (Linearity)
L. Assumption of Constant Variability
M. Assumption of Normality
N. Normal PPlot
O. Assumption of Independence
P. DurbinWatson Statistic
Q. Relevant range
R. Outlier(s)
S.
Curvilinear Regression
T.
Dummy Variable Regression
U. Multicollinearity
V.
Interaction
W. Stepwise Regression
You are working on a regression study and you have the following situations in which
you need use your expertise in statistics. For each of the next questions, choose the
most appropriate term above that best fits the situation.
Choose only one and write
the letter in the space provided below the question.

SCENARIOS
1. This measure of strength allows you to tell which variables in a multiple regression are not useful
in the multiple regression equation.
1
.
2.
What do you call it when you have independent variables that are highly related with each other?
2.
3.
What graph or measure would be useful to you in checking the assumption of independence?
3
.
4.
You can use this measure to help with multicolinearity problems.
4
.
5.
You have several variables to use as explanatory variables and you want some way to narrow
down your choices from the many different models that you could use.
5.
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We have covered various tests and confidence intervals and many of these are listed below. Read
the following short scenarios and pick the test or confidence interval that best meets the
objective in the scenarios that follow.
Choose only one and write the number in the space
provided below the question.
1. Confidence interval for a proportion.
2. Confidence interval for a mean
3. Test for a population Proportion
4. Test for comparing Proportions between 2 groups.
5. Test for comparing Proportions between c groups. (c>2)
6. Test for no relationship between 2 categorical variables.
7. Test for a Population Mean
8. Test for Means comparing 2 groups.
9. Test for Means comparing c groups.
(c>2)
10. TukeyKramer Procedure for Means.
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 Spring '08
 Abousayf,F
 Statistics, Regression Analysis, upper critical value, MBA program

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