MBA 510

Answers to FAQs about Exercise #3.

Link to Exercise #3

Link to MBA 510 Main Page

Q.: Does a 4 point increase mean 4 percentage points (0.04),
or decimal

points (0.4), or 4 units?

A.: I meant 4 units. Such as a change in pressure
from 28"Hg to 32"Hg.

Q: Won't that give me a very large number for the odds
ratio, R?

A.: Well, yes. Even though I asked for the effect
of a 4-point change

in Pressure on the probability, just give me the effect
on the odds

ratio, R. Our calculators probably don't show enough
digits to see the

difference in the probabilities.

Q: What do you mean by "the effect of a 4 point increase
in Pressure?"

Am I supposed to go back and add 4.0 to all of the values
in the Pressure

column in the data table?

A.: No. I want you to predict the effect of a hypothetical
change in

Pressure, assuming that Temp and Humidity remain

constant. In the logistic regression you do this
by using the

odds-ratio equation. Note that the effect is a
multiplicative effect;

that is, you should give me a factor by which the odds
ratio will be

multiplied as a result of a 4 point increase in Pressure.
In the linear

regression, you should give me the predicted numerical
change in Y

(which is supposed to be 0 or 1, but the predicted values
probably won't

be) as a result of a 4 point change in Pressure.
You should use the

coefficients in the Paremeter Estimates section to form
the regression

equation to help you answer this.

Q.: Why would we want to use a level of significance
(alpha, a) of 8%

in the linear regression?

A.: My mistake. I should have inserted that
sentence in the logistic

regression section. I was looking at the p values
from the Wald

chi-square statistics in the Parameter Estimates section.
The

maximum-likelihood tests are usually better, and they
don't require an

8% alpha.

Q.: But I didn't find a difference in the significant
variables between

the two regressions. Should I still answer question
7?

A.: Yes, but if you found that the same two variables
were significant

in each model, you should still tell me which model is
better and why it

is better. If you used the p values from the maximum-likelihood
tests

for the logistic regression, you may find that the same
two variables

are significant in each model. I was thinking of
the Wald tests given

in the Parameters Estimates section when I wrote that
question.

created April 18, 2001, by James R. Frederick