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- IBM SPSS Statistics Standard v27 Campus Edition
IBM SPSS Statistics Standard v27 Campus Edition
Out of stock
| SKU | D0FDMLL |
|---|---|
| Status | Enabled |
IBM SPSS Statistics Standard Edition
Boost your analytics with regression, custom tables and advanced statistics features
What SPSS Statistics can do for your business
IBM® SPSS® Statistics Standard Edition includes all the Base Edition capabilities plus features that support advanced modeling options, regression analysis and custom tables.
Take advantage of various regression procedures including logistic regression, quantile regression and more. You can leverage several advanced statistics procedures including GLM multivariate, variance components analysis, life tables, Bayesian statistics to name a few. Additionally, you can summarize your data and display analyses in production-ready tables with the Custom Tables module.
Feature spotlights
Regression
SPSS Regression enables you to predict categorical outcomes and apply various nonlinear regression procedures.
Bayesian statistics
Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more information becomes available.
Multivariate general linear modeling (GLM)
GLM multivariate modeling is used to model value of multiple dependent variables based on their relationships to categorical and scale predictors. GLM repeated measures allows repeated measurements of multiple dependent variables.
Custom tables
Summarize SPSS Statistics data, and display your analyses as presentation-quality, production-ready tables. With analytics capabilities and advanced features, you can build tables to interpret and learn from data.
Generalized linear models and generalized estimating equations
The generalized linear models procedure expands the general linear model so that the dependent variable is linearly related to the factors and covariates through a specified link function. Using the generalized estimating equations procedure, you can analyze repeated measurements or other correlated observations.
Survival analysis
Use life tables to examine the distribution of time-to-event variables, including by levels of a factor variable; Kaplan-Meier survival analysis for examining the distribution of time-to-event variables, including by levels of a factor variable or producing separate analyses by levels of a stratification variable; and Cox regression for modeling the time to a specified event, based upon the values of given covariates.