First, determine whether the data in the exercises meet the following assumptions of the statistic: 

• Data must be in frequency form (nominal data)
• Individual observations must be independent (no double testing)
• Each observation must fall in only one cell (discreteness)
• Sample size must be adequate (observations greater than 20 for 2X2 table, for larger tables no more than 20% of cells can have expected values less than 5). In 2X2 tables, Yates Correction is automatically applied. 

To do the Pearson Chi-Square

1. Get your data files ready
2. Select "Analyze" then "Descriptive Statistics" then "Crosstabs"
3. Select row and column variables with the arrow buttons
4. Select "Statistics" (Chi-square)
5. Select "Cells" (Expected and Observed.)

A typical SPSS output on chi-square is shown below: 

            Count  |
           Exp Val |
                   |                    Row
                   |     .00|    1.00| Total
COURSE     -----------------|--------|
              .00  |    11  |     9  |    20
                   |  10.0  |  10.0  | 50.0%
                   |-----------------|
             1.00  |     9  |    11  |    20
                   |   10.0 |  10.0  | 50.0%
                   -------------------
            Column      20       20       40
             Total   50.0%    50.0%   100.0%

Chi-Square                 Value           DF          Significance
Pearson                   .40000            1                .52709
Continuity Correction     .10000            1                .75183
Likelihood Ratio          .40067            1                .52674
Mantel-Haenszel test for  .39000            1                .53230
      linear association

Minimum Expected Frequency -   10.000

Number of Missing Observations:  0