Frequencies, in statistics, refers to counts of categories or responses. It's a basic statistical tool that provides a sense of how often specific response options occur in a population.

Using the sample data set, let's say we want to know the geographic distribution of genetic counselors. In the sample data set there is a variable that codes for geographic region, "region." Using the frequencies function in SPSS, we can get a sense of the geographic distribution of genetic counselors.

To do so, begin by selecting "Analyze" -> "Descriptive Statistics" -> "Frequencies":

The "Frequencies" window will appear:

Scroll through the variables until you find the variable you want. In our example, we're using "region." Use the arrow to move it into the "Variable(s):" box:

Once you've done that, you don't actually need to do anything else except make sure that the "Display frequency tables" box is checked. Then hit "OK". In the Output Window you should see something like the following:

There are two tables in this output. The first gives a summary of the cases included. The "Valid" N tells you how many of your cases had a response to this variable that is not marked as missing. The "Missing" N indicates the number that are missing.

The second table is called a frequency table of frequency distribution. It includes four columns. The first, labeled "Frequency," simply reports the total number of cases that fall into each category of the variable of interest, "region." For instance, 100 genetic counselors live in the "pacific" region. The second column, labeled "Percent," provides a percentage of the total cases that fall into each region. The percentage of genetic counselors that work in the "pacific" region is 15.3%. The third column, labeled "Valid Percent," is a variation of the "Percent" column; it recalculates the percent without including the missing cases. The fourth column, labeled "Cumulative Percent," adds the percentages of each region from the top of the table to the bottom, culminating in 100%. This last column is more useful when you have ranked or ordinal variables you are analyzing as it makes it easy to get a sense of what percentage of cases fall below a specific rank.

The above example should help illustrate the utility of calculating frequencies in SPSS.