Cross Tabulation
Cross Tabulation (Chi-Squared)
Introduction
Cross
Tabulation is a powerful technique that helps you to describe the relationships between categorical (nominal
or ordinal) variables. With Cross Tabulation, we can produce the following
statistics:
- Observed Counts and Percentages
- Expected Counts and Percentages
- Residuals
- Chi-Square
- Relative Risk and Odds Ratio
for a 2 x 2 table
- Kappa Measure of agreement for
an R x R table
Examples
will be used to demonstrate how to produce these statistics using SPSS. The
data set used for the demonstration comes with SPSS and it is called GSS93.sav.
It has 67 variables and 1500 cases (observations). Open this data file which is
located in the SPSS folder. Study the data file in order to understand it
before performing the following exercises.
Exercise 1: An R x C Table with Chi-Square Test of Independence
Chi-Square
tests the hypothesis that the row and column variables are independent, without
indicating strength or direction of the relationship. Like most statistics
test, to use the Chi-Square test successfully, certain assumptions must be met.
They are:
- No cell should have expected
value (count) less than 0, and
- No more than 20% of the cells
have expected values (counts) less than 5
In
the SPSS file, there is a variable called relig short for
religion (Protestant, Catholic, Jewish, None, Other)
and another one called region4 (Northeast, Midwest, South, West).
In this example, we want to find out if religious preferences vary by region of
the country.
To
produce the output, from the menu choose:
- Analyze -> Descriptive
Statistics -> Crosstabs….
- Row(s): Religious Preferences
- Column(s): Region [region4]
- Statistics… select Chi-Square, click Continue then OK
