Frequency analysis with SPSS

In my previous article “Introducing Data” we discussed about importing files and creation of data sheet in SPSS.  Moving further, in this article I will be discussing about the most basic technique which can be applied within SPSS i.e. Frequency analysis.

Running the frequency analysis test

After entering the data, click on “Analyze”, then “Descriptive Statistics”, and then “Frequencies”.

When you run a procedure in SPSS, such as frequencies, you need to select the variables in the dialog box.  On the left side of the dialog box, you see the list of variables in your data file.  You click a variable name to select it, and then click the right-arrow button to move the variable into the Variable(s) list.

Run a procedure in SPSS
Figure 1

Then click on statistics shown in the Figure 1 and a new window will open as shown below (Figure 2):

Click on statistics
Figure 2

Based on your requirement you can select the Test Statistic i.e. Mean, Median, Mode etc (See article “Basic Terms of SPSS”). Then you select it by placing a check in the available box next to the statistic.  Then click ok and you will return to the main frequencies box i.e. Figure 1.

Once you click “OK”, output will be displayed as shown in the Figure Given below:

Table 1
Table 1

If you want to modify data manually in the tables:

If you want to change the data in the tables [i.e. the spss viewer], you need to double click a pivot table (Table 1) in order to activate it so that you can make modifications.  When activated, it will appear to have “railroad track” lines surrounding it.  Double-click to activate an object for editing.  If the object is a pivot table, you can obtain detailed help on items within the table by right-clicking on row and column labels after the table is activated.

Interpreting multivariate analysis with more than one dependent variableCross tabulation in SPSS

Priya Chetty

Partner at Project Guru
Priya is a master in business administration with majors in marketing and finance. She is fluent with data modelling, time series analysis, various regression models, forecasting and interpretation of the data. She has assisted data scientists, corporates, scholars in the field of finance, banking, economics and marketing.
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