SPSS descriptive statistics are designed to give you information about the distributions of your variables. SPSS allows you to complete a number of statistical procedures including: measures of central tendency, measures of variability around the mean, measures of deviation from normality, and information concerning the spread of the distribution.
For the following instructions:
* = A single click of the left mouse button
**= A double-click of the left mouse button
After opening the file you desire to use, * Analyze, Descriptive Statistics, *Descriptives. See here.
Select the variables for which you wish to compute descriptives by clicking the desired variable name in the box to the left and then pasting it into the Variables box to the right by clicking the right arrow in the middle of the screen. See here.
If you want to calculate more than four statistics, after selecting the desired variables (and before *OK), *Options. To select the desired descriptive statistics, * on the box next to the procedure you wish to have completed. Under Descriptives: Options, you can choose a number of statistics. By clicking on the box next to the option, SPSS can perform many different functions. See here.
- Some additional SPSS features include:
- Under the Descriptives: Options, you can also choose the Display Order options (again by
* on the the circle next to the option):
- Variable list: This is the default for this option; this arranges the items in the same order
as found in the data editor).
- Alphabetic: Names of variables are arranged alphabetically.
- Ascending means: This orders the means from smallest mean value to largest mean
value in the output.
- Descending means: This orders the means from largest mean value to smallest mean
value in the output.
Kinds of descriptive statistics that SPSS provides
Measures of Central Tendency
Central tendency measures give an estimate of how a group did as a whole
- Mean: the average value of the distribution
- Median: the middle value of the distribution
- Mode: the most frequently occurring value
***Note that to calculate both median and mode of your distribution, you
need to *Analyze, *Descriptive Statistics, and then *Frequencies. Then * on the boxes of Median
and/or Mode under "Central Tendency."
***Note also that percentiles and quartiles are done under frequencies
too. See here.
Measures of Variability
Variability provides an estimate of how much scores within a group of scores varied. In SPSS they can be found under the "Analyze", "Descriptive Statistics" menus in either the Descriptive or Frequency options. . See here & See here.
- Measure for the size of the distribution:
- Maximum: largest value in the distribution
- Minimum: smallest value in the distribution
- Range of values in the distribution
- Sum of the scores in the distribution
- Measures of stability: Standard error
- Standard error is designed to be a measure of stability or of sampling error.
- SPSS computes SE for the mean, the kurtosis, and the skewness
- A small value indicates a greater stability or smaller sampling err
Measures of the shape of the distribution
(measures of the deviation from normality)
- Kurtosis: a measure of the "peakedness" or "flatness" of a distribution. A kurtosis value near zero indicates a shape close to normal. A negative value
indicates a distribution which is more peaked than normal, and a positive kurtosis indicates a shape flatter than normal. An extreme positive kurtosis indicates a distribution where more of the values are located in the tails of the distribution rather than around the mean. A kurtosis value of +/-1 is considered very good for most psychometric uses, but +/-2 is also usually acceptable.
- Skewness: the extent to which a distribution of values deviates from symmetry around the mean. A value of zero means the distribution is symmetric, while a positive skewness indicates a greater number of smaller values, and a negative value indicates a greater number of larger values. Values for acceptability for psychometric purposes (+/-1 to +/-2) are the same as with kurtosis.
No skew (lopsidedness of the distribution)
mean > median = positive skew
mean < median = negative skew
No kurtosis (peakedness or flatness)
negative value (very flat) is undesirable
positive value (very pointed) is also undesirable
Skew and Kurtosis in SPSS
Choose Statistics, Descriptives
Select skew and kurtosis
Interpretation of Skew and Kurtosis Output
Divide Skew by SE Skew and divide Kurtosis by SE Kurtosis
Values of 2 or more suggest skew or kurtosis
Viewing Normality of Distribution
Choose Charts, Histogram
Check "Display normal curve"
Creating Standard Scores
A z-score is a standard score obtained by subtracting the mean from a score and dividing by the
In SPSS, Compute a new variable
Or, choose Descriptives and "save standardized values as variables". See here.
Comparing means allows us to look at differences between groups of participants
Choose Statistics, Compare Means, Means
Continuous variables go in Dependent List
Grouping variable goes in Independent List
Under "Options," choose statistics
Enter second categorical variable as layer
Plotting Group Means
Choose Graphs, Bar, Simple, Define
Choose "Other summary function" and enter dependent variable
Independent variable is "Category Axis"
Under "Options," uncheck "Display groups defined by missing values"
A Clustered Chart can be used for a second grouping variable
After completing the desired descriptives, *Continue, *OK. The results of the just-completed analysis will be included in the top window, labeled Output - SPSS Output Navigator.