EXERCISE 13.1
Show that the matrices

and

have an eigenvalue
equal to

and that the corresponding eigenvectors are proportional to

.
EXERCISE 13.3
Do a correspondence analysis for the car marks data (Table
B.7)!
Explain how this table can be considered as a contingency table.
EXERCISE 13.4
Compute the

-statistic of independence for the French
baccalauréat data.
EXERCISE 13.5
Prove that

and

and verify (
13.20).
EXERCISE 13.6
Do the full correspondence analysis of the U.S. crime data
(Table
B.10), and determine
the absolute contributions for the first three axes. How can you
interpret the third axis?
Try to identify the states with one of the four regions to which it belongs.
Do you think the four regions have a different behavior with respect to
crime?
EXERCISE 13.7
Repeat Exercise
13.6 with the
U.S. health data (Table
B.16). Only analyze the columns
indicating the number of deaths per state.
EXERCISE 13.8
Consider a

contingency table being a diagonal matrix

.
What do you expect the factors

to be like?
EXERCISE 13.9
Assume that after some reordering of the rows and the
columns, the contingency table has the following structure:
That is, the rows

only have weights in the columns

,
for

. What do you expect the graph of the first two factors
to look like?
EXERCISE 13.10
Redo Exercise
13.9 using the following contingency table:
EXERCISE 13.11
Consider the French food data (Table
B.6).
Given that all of the
variables are measured in the same units (Francs), explain
how this table can be considered as a contingency table.
Perform a correspondence analysis and compare
the results to those obtained in the NPCA analysis in Chapter
9.