# Cross tabulation in SPSS

A cross tabulation is a joint frequency distribution of cases based on two or more categorical variables.

Open the SPSS file and CLICK on Analyze. Under that CLICK on Descriptive statistics and then select cross tabulation (See Figure 1).

Once you Click on “Cross tabulation”, a new dialog box would open, (See Figure 2). Here you will see two boxes, Rows and Columns. You can select one or more than one variable in each of these boxes (Row and Column box). This depends on what you have to compare. Then click on “OK”.

If you need more detailed results then Click on “Statistics” (See Figure 2). A new dialog box would open wherein you can select several statistical tools depending on the requirement of the research query.

The Table 1 below shows a cross-tabulation that contains information solely on the number of cases that meet both criteria, but not a % distribution.

## Percentages in cross tabulation

The above information, i.e. the counts in the cell are the basic elements of the table. However they are usually not the best choice for reporting findings because they cannot be easily compared if there are different totals in the rows and columns of the table. For example, if you know that 17 Males and 24 Females like rap music very much. Then you can conclude little about the relationship between the 2 variables unless you also know the total of men and women in the sample.

In order to calculate the percentages, CLICK on “Analyze”, then “Descriptive Statistics”, then “Crosstabs”, then “Cells” and under “Percentage” select all three options. (As can be seen in Figure 2 above):

Row %: the cell count divided by the number of cases in the row times 100

Column %: the cell count divided by the number of cases in the column times 100

Total %: the cell count divided by the total number of cases in the table times 100

The 3 criterias % stated above convey different information, so be sure to choose the correct one for your problem. If one of the 2 variables in your table can be considered an independent variable and the other a dependent variable, make sure the % sum up to 100 for each category of the independent variable (see Table 2 below).

Note:Do not be alarmed if the marginal in the cross-tabulation aren’t identical to the frequency tables for the individual variables. Only cases with valid values for both variables are in the cross-tabulation. Therefore if you have cases with missing values for one variable but not the other, they will be excluded from the cross-tabulation. Respondents who tell you their gender but not their attitudes about rap music are included in frequency table for gender. However they are not included in the cross-tabulation of the 2 variables.

Row %: With reference to above example (Table 2), when we divide the count for Males who “Like very much” (i.e. 17) with the total number of Males (i.e. 615), the result is 2.8% (% within respondent’s sex). (17 and 615 are horizontal, therefore become “row%”).

Column %: With reference to above example (Table 2), when we divide the count for Males who “Like very much” (i.e. 17) with the total number of people who “Like very much” (i.e. 41), the result is 41.5% (% within rap music). (17 and 41 are vertical, therefore become “column%”).

Since gender would fall under the realm of an independent variable, you want to calculate the row %. This is because they will tell you what % of women and men fall into each of the attitudinal categories. This % isn’t affected by unequal numbers of males and females in your sample. From the row % displayed above, you find that 2.8% of males like rap music very much as do 2.9% of females. So with regard to strong positive feelings about rap music, you note that there are no visible differences.

Note:Cross tabulation results do not examine the statistical differences. From the column% displayed above, you find that among those who like rap music very much, 41.5% are men and 58.5% are female. This does not tell you that females are significantly more likely to report liking rap music very much than males. Instead, it tells you that of the people who like rap music very much, women tend to hold a stronger view than men.

The column % depend on the number of men and women in the sample as well as how they feel about rap music. If men and women have identical attitudes but there are twice as many men in the survey than women. In such case the column % for men will be twice as large as the column % for women. You can’t draw any conclusions based on only the column %.

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