8/6/2019 Modeling Snap Test1
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ModelingSnap Test 1
Give short answers:
1. In a Multiple Linear model E(y|X)= 0 + 1X1 + 2X2 ++ KXK+,
What does i , i>0 captures?
2. Consider the model E (y|X) = 0 + 1X1 + 2X2 +, where y =
Sales, X1= Advertisement expenses
and X2 = Season, if the 95% confidence interval estimate for 1
is (1256.3, 2133.2), How will youinterpret this confidence interval
in terms of Sales and Advertisement Expenses?
3. Define R 2, If R2 = 0.74, How will you interpret this
value?
4. What is the logic behind using F- test as a Test for overall
fit of the model?
5. If the P value for testing the coefficient of a explanatory
variable (X1 ) is 0.00001, State the nulland alternative hypothesis
and give your conclusion.
6. If a Categorical variable classifies into m categories and if
you introduce m dummy variables forthose m categories, what problem
will you end up with?
7. Consider a multiple linear regression model with Y=income and
X1= Gender and X2 = MaritalStatus,
(i)Specify the model by defining the Dummy variables
(ii) What is the bench mark category?
(iii) Interpret the Slope and intercept terms(iv) Define
Interaction Effect, How will you study interaction effect between
X1 and X2?
8. (i) Define Multicollinearity,(ii)What are the consequences of
perfect multicollinearity and near multicollinearity?
(iii)VIF is a measure of multicollinearity, Justify
(iv) Suggest few ways of overcoming multicolinearity
9. Consider the model ++
=110 XeY , Is this model Linear in Parameter? If the given model
is not
linear in parameter what transformation you can do to make the
model Linear in parameter?
10. Consider a data set named Sales_Details containing Y =
Sales, X1= Advertisement expenses
and X2 = Season, Write SAS Code for obtaining a Regression of X1
, X2 on Y with VIF and
Confidence limits for the Parameter Estimates as additional
measure in the output.
