POLS 6482 ADVANCED MULTIVARIATE STATISTICS
Fourth Assignment
Due 1 October 2001
This Homework assumes that you have read Chapters I and II of the Epple Notes!
This problem is a continuation of the party identification problem that
was part 1 of the 2nd Homework Assignment.
Compute the correlation matrix for the variables
education,
income, and
age for both the 1968 and 1996 datasets.
Interpret the changes in the correlations between 1968 and 1996. Do the
changes make sense to you? Why? Why not?
Find the eigenvalues and eigenvectors of the correlation matrix for
both 1968 and 1996. Use the method shown in 3.b. of the 2nd
homework.
This problem is a continuation of 1.c of the 3rd
homework. Bring up the EVIEWS version
of HDMG105X.DTA from the 3rd homework. Run the regression:
LS clint96 C black south hisp income rep
and save the residuals by copying them to another vector; namely:
genr clintresid=resid
Compute the correlation matrix between
clintresid,
black,
south,
hisp,
income, and
rep. What should the values of the correlations
between clintresid and the other variables be?
Why?
In EVIEWS you can generate the
fitted values of the dependent variable (the y-hats) with the forecast
command. For the regression above:
forecast clintyhat
and EVIEWS puts the y-hats into the vector
clintyhat. (In Stata
the corresponding command is predict clintyhat.)
Calculate the correlation between
clintyhat,
clintresid,
black,
south,
hisp,
income, and
rep. What should the values of the correlations
between clintyhat and the other variables be?
Why?
In EVIEWS use the HIST command
on clintresid. What famous probability distribution does
the histogram look like?
In EVIEWS use the SCAT command
to get scatterplots of clintresid versus
black,
hisp, and
income. The syntax of the command is:
scat black clintresid
which makes black the "x" axis and
clintresid the "y" axis of the scatterplot.
Do these scatterplots look random to you?
In EVIEWS run the regression:
LS clint96 C clintresid
Compare the coefficients and r-square to the original regression. Explain the values
of the coefficients. Explain the value of the r-square.