**Homework
#11**

**SPSS
Statistical commands: CROSSTABS**

**(15 pts)**

For this assignment, you will be
performing what most statistics texts call a Chi-square analysis. You may also
hear others refer to it as a "crosstabulation" or
"crosstabs." This analysis is
simple and requires only ** "qualitative"**
variables. If the two variables are
qualitative

a. **Your research question**. This includes the variables you are studying
and how you think they may be related.

b. **The obtained result of the analysis**: What is the Chi-square value and the
significance level? Is it statistically
significant? What is the phi
coefficient value? Are there any
significant standardized residuals?

c. **A verbal description of the results**. In “English,” describe what you found.

**Questions
to ask yourself when doing a chi-squared statistical analysis** (especially
useful for part b)

1.
**Is the
relationship statistically significant?**
Look at the Chi-square statistic and its corresponding p-value.

2.
**How strong is
the relationship?** Look at the phi
coefficient.

3.
**Where is the
relationship?** Look at the
standardized residuals.

In the real world, the answers to
questions 2 and 3 are important ONLY if you answer Yes to question 1. However, for homework, you must report the
answers to all three questions. It’s
good for you!!

**Procedure:**

a. Have SPSS
open your survey.sav file.

b. Choose: *Analyze,* *Descriptive Statistics*, *Crosstabs*

c. Specify a
variable to be the row and then specify a variable to be the column. SPSS will
do many crosstabs if you specify many variables. For our purposes, just do two
at a time. The statistical procedure doesn't care which variable you specify
for the column versus row. Rules of thumb:
the variable with fewer categories should be the column; the variable
for which you want to make comparisons (e.g., male vs. female) should be the
column. Remember, it doesn't matter for statistical purposes.

d. Choose the *Statistics* that will tell you whether
the variables are significantly related. Choose Chi-square for the chi-square
statistic and probability value. Choose Phi tell you how strongly the variables
are related (this is a type of correlation coefficient that ranges from 0.00 to
1.00).

e. Choose *Cells* to specify the output in the
cells. For Count, by default you get the observed frequencies. You should also
specify expected frequencies and standardized residuals. If you like, you can have SPSS print out the percentage: you should specify Row, Column and/or Total.
The least useful is Total. Take good notes in class, play with the numbers, and
figure out how to interpret the percentages. This is very important. **Be
sure and check the Standardized Residual box**!!

f. OK will
execute the Crosstabs.

Example Analysis:

a. Research
Question

I want to
examine whether lurkers are more likely to use private email to communicate
with others. Do lurkers privately email
more than posters?

b. Analysis

The
Chi-square analysis shows that there is a significant relationship between
lurking and privately emailing others in the group, c^{2}(1) = 21.27, p
<.05. The phi correlation coefficient was .71. The strength of this
relationship is strong. The standardized residual for the lurkers who privately
email is 2.5; therefore, it is significant.

OR

The relationship is not significant, c^{2}(1) = 1.47, p=.23.
The phi correlation coefficient was .19. The strength of this relationship is weak. No standardized
residuals were greater than 2.0.

Note that I’ve used p< .05 and p=.23.
You can use either system. You
can give the exact probability to no more than three decimals -- p = .023, but
two decimal places, p= .02 is also
acceptable. .

NOTE: The (2) is **the degrees of freedom** for the test (Rows-1 * Columns-1).

c. Interpretation

More
lurkers used private email than were expected, if there was no relationship
between the variables. Therefore,
lurkers are more likely to use private email to communicate with others in
their virtual community than non-lurkers (i.e., posters).

OR (say this if
there is NOT a significant relationship.)

Lurkers and
posters used private email to communicate with others in their group at about
the same rate. Therefore, there was not
a difference between lurkers and non-lurkers (i.e., posters) in using private
email.

**Assignment**

Use the CROSSTABS command to analyze at
least three research questions concerning the relationship among qualitative or
limited range "quantitative" variables. THIS IS VERY IMPORTANT! **IF YOU DO A CROSSTAB ON A CONTINUOUS OR
LARGE RANGE QUANTITATIVE VARIABLE, THAT IS WRONG!!!** Describe (using a word processor) each
analysis using the format of the example analysis described above (i.e., a
research question, analysis and interpretation). Attach the appropriate printout to the back of the questions. Feel free to do more analyses, try out the
way that CROSSTABS works, spend some time figuring out the difference between
row, column, and total percentages.
Before you start, make sure you understand (really “get”) what variables
we have in our survey and which ones you can use.

Note:
Figuring out the source of the percentages in the tables is very
important. A standardized residual of
greater than 2.00 generally indicates a significant difference in that
particular cell.

Print your output. You can print
directly from SPSS by choosing File, then Print. However, you can also save
your output as a .lst file. When SPSS asks if you want to save your output,
indicate yes and then provide a file name on your diskette. You can edit as
much as you like and print from the word processing program.

Exit from SPSS: Unless you have changed your .sav file with
additional recodes, computes, etc., you do not need to save the data window.
Saving the output window is covered above.

Separate all printouts and attach to
your analyses..

If you have problems interpreting
crosstab output, send an e-mail question.

Note: You should get into the practice
of using superscript to type c^{2}. You can also have your word processing
program insert a special graphic symbol for the Greek letter c.