Options include bar charts, pie charts, and histograms. In general, you should never use any of these statistics for dichotomous variables or nominal variables, and should only use these statistics with caution for ordinal variables.Ĭ Charts: Opens the Frequencies: Charts window, which contains various graphical options. It is up to the researcher to determine if these measures are appropriate for their data. SPSS will compute those statistics if they are requested, regardless of whether or not they are meaningful. If your categorical variables are coded numerically, it is very easy to mis-use measures like the mean and standard deviation. For example, this would be the case if you had measured subjects' ages and had coded anyone between the ages of 20 and 29 as 25, or between the 30 and 39 as 35 (source: IBM SPSS Statistics Information Center). The Values are group midpoints option can be applied to certain ordinal variables that have been coded in such a way that their value takes on the midpoint of a range.The Mode (which is the most frequent response) has a clear interpretation when applied to most nominal and ordinal categorical variables.The vast majority of the descriptive statistics available in the Frequencies: Statistics window are never appropriate for nominal variables, and are rarely appropriate for ordinal variables in most situations. Moving several variables to this box will create several frequency tables at once.ī Statistics: Opens the Frequencies: Statistics window, which contains various descriptive statistics. To include a variable for analysis, double-click on its name to move it to the Variables box. To run the Frequencies procedure, click Analyze > Descriptive Statistics > Frequencies.Ī Variable(s): The variables to produce Frequencies output for. In SPSS, the Frequencies procedure can produce summary measures for categorical variables in the form of frequency tables, bar charts, or pie charts.
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