# Cross tabulation in SPSS

By Priya Chetty on January 26, 2015

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 dialogue 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 boxes). 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 dialogue box would open wherein you can select several statistical tools depending on the requirement of the research query.

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 criteria % 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 % sums up to 100 for each category of the independent variable (see Table 2 below).