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SPSS Statistics Commonly Used Analyze Menus

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2020-08-15 16:59:11
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The following table provides a list of some of the most commonly used procedures in the Analyze menu in SPSS Statistics.
Menu Submenu Useful For
Code Book Reports Provides a quick look at all your variables at once. The level of measurement automatically controls which summary statistics are displayed.
Frequencies Descriptives Tells you how many of each category value you have. Most useful for categorical variables because you can run all of them at once.
Descriptives Descriptives Gets basic scale variable information, such as the mean and standard deviation.
Explore Descriptives Based on a famous book, Exploratory Data Analysis, looks at all kinds of variables as well as pairs of variables.
Crosstabs Descriptives Tests 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 variables.
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 income).
Paired Samples T-Test Compare Means Tests whether a significant difference exists in the mean under two conditions (for example, before versus after, or standing versus sitting).
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 Determines the similarity in the way two continuous variables change in value from one case (row) to another through the data.
Linear Regression Regression Predicts a continuous dependent variable from one or more continuous independent variables
One Sample Nonparametric Tests Compares the distribution of a categorical dependent variable to population norms.
Independent Samples Nonparametric Tests Tests whether the means or medians for two or more different groups differ on a dependent variable.
Related Samples Nonparametric Tests Tests whether the means or medians of the same group differ under two conditions or time points.
Univariate General Linear Model An extension of one-way ANOVA in which there is more than one independent variable.
Multivariate General Linear Model An extension of one-way ANOVA in which there is more than one dependent variable.
Repeated Measures General Linear Model An extension of the paired-samples t-test in which the same group is assessed under two or more conditions or time points.
Binary Logistic Regression Used in situations similar to linear regression but the dependent variable is dichotomous.
Multinomial Logistic Regression An extension of binary logistic regression in which the dependent variable is not restricted to two categories.
Discriminant Classify Builds a predictive model for group membership based on the linear combinations of predictors that best separate the groups.

About This Article

This article is from the book: 

About the book author:

Keith McCormick has traveled the world speaking at conferences teaching machine learning, data science, and SPSS. He currently serves as executive data scientist in residence at Pandata. Hundreds of thousands have watched his LinkedIn Learning courses.

Jesus Salcedo, PhD, studied psychometrics at Fordham and has been using SPSS for over 25 years. Currently at Wiley, he served as the SPSS curriculum lead at IBM and has trained thousands of users.