SPSS Statistics Commonly Used Analyze Menus
The following table provides a list of some of the most commonly used procedures within the Analyze menu of IBM SPSS Statistics, which is an application that performs statistical analysis on data.
|Submenu||Useful For . . .|
|Code Book||Reports||A quick look at all your variables at once. Level of
measurement automatically controls which summary statistics are
|Frequencies||Descriptives||Most useful for categorical variables. You can run all of them
at once. Tells you how many of each category value you have.
|Descriptives||Descriptives||Easy way to get basic scale variable info like mean and
|Explore||Descriptives||Based on a famous book, Exploratory Data
Analysis. An effective way to look at all kinds of
variables, as well as pairs of variables.
|Crosstabs||Descriptives||A test to check to see if categorical variables are independent
of each other or related to each other.
|Means||Compare Means||Calculates subgroup means and related statistics for dependent
variables within categories of one or more independent
|One-Sample T-Test||Compare Means||Tests whether the mean of a single variable differs from a
specified value (for example a group using a new learning method
compared to the school average).
|Independent Samples T-Test||Compare Means||Tests whether the means for two groups differ on a continuous
dependent variable (for example, females versus males on
|Paired Samples T-Test||Compare Means||Tests whether there is a significant difference in the mean
under two conditions (for example, before versus after, or standing
|One way ANOVA||Compare Means||Tests whether the means for two or more groups differ on a
continuous dependent variable (for example, drug1 versus drug2
versus drug3 on depression).
|Bivariate Correlation||Correlate||Correlations determine the similarity or difference in the way
two continuous variables change in value from one case (row) to
another through the data.
|Linear Regression||Regression||A statistical technique that is used to predict a continuous
dependent variable from one or more continuous independent