Discriminant - Offers a choice of variable selection methods. TwoStep Cluster Analysis - Group observations into clusters based on nearness criterion, with either categorical or continuous level data. Hierarchical Cluster Analysis - Used to identify relatively homogeneous groups of cases. K-means Cluster Analysis - Used to identify relatively homogeneous groups of cases based on selected characteristics. Explore - Confidence intervals for means M-estimators identification of outliers plotting of findings. Nonparametric tests - Chi-square, Binomial, Runs, one-sample, two independent samples, k-independent samples, two related samples, k-related samples. Correlation - Test for bivariate or partial correlation, or for distances indicating similarity or dissimilarity between measures. ANOVA and ANCOVA - Conduct contrast, range and post hoc tests. Compare means - Choose whether to use harmonic or geometric means and much more. Descriptive ratio statistics - Coefficient of dispersion, coefficient of variation, price-related differential and average absolute deviance. Descriptives - Central tendency, dispersion, distribution and Z scores. Frequencies - Counts, percentages, valid and cumulative percentages central tendency, dispersion, distribution and percentile values. Includes these statistical tests: Crosstabulations - Counts, percentages, residuals, marginals, tests of independence, test of linear association, measure of linear association, and much more.
IBM SPSS GRAD PACK PREMIUM FULL VERSION
Includes two add-ons in addition to the full version of SPSS Base: Advanced Statistics and Regression. All contents under (CC) BY-NC-SA license, unless otherwise noted.THIS PRODUCT IS FOR SALE TO CURRENT COLLEGE STUDENTS AND TEACHERS ONLY. Missing value analysis (with multiple imputation) to address issues of “dirty data” for more complete analysis and better decision-makingĪdvanced data preparation to identify anomalies and the other data that can skew resultsĭecision trees to better identify groups, discover relationships between groups, and predict future eventsįorecasting to predict trends and build expert time-series forecasts quickly and easilyĬategories to obtain clear insight into complex categorical and numeric data, as well as high dimensional data.īootstrapping to test the stability and reliability of predictive modelsĪdvanced sampling assessment and testing proceduresĭirect marketing and product decision-making procedures to identify best customers and the product attributes that appeal to themĬopyright © Melinda Higgins, Ph.D. High-end charts, graphs and mapping capabilities to aid analysis and reporting Simulation modeling to build better models and assess risk when inputs are uncertainĬustomized tables to analyze and report on numerical and categorical data (not available in Statistics Standard Grad Pack Edition) Nonlinear regression, including MLR, Binary Logistic Regression, NLR, CNLR and Probit Analysis, to improve the accuracy of predictions
Seamless integration with R, Python and other environments to easily and effectively expand statistical capabilities and programmabilityĪdvanced statistical procedures, including GLM, GLMM, HLM, GENLIN and GEE to more accurately identify and analyze complex relationships Here is a quick comparison between the 3 editions (available at this reseller ) FeaturesĬore statistical and graphics capabilities to take standard analytic projects from start to finish However, it is recommended to purchase the Premium Grad Pack which also includes bootstrapping, missing data analysis, customized tables, and other helpful tools. The Standard edition would be the minimal version to purchase as it has the necessary statistical modeling procedures included. The Premium edition (approximately $89).The Standard edition (approximately $49) and.There are several links at this website for purchasing students versions of SPSS. Go to IBM’s website for student grad pack versions at
Discriminant Analysis/MANOVA, Mediators and SEM Multilevel (Mixed or Nested) Linear Models (MLM) Dependent/Paired data and Repeated Measures Logistic & Poisson Regression - Generalized Linear Regression Modeling Covariates and Interaction/Moderator Effects Interactions, Moderators, Covariates, Factors 14,15 Regression Diagnostics and Variable Selection (cont'd).Multivariate Regression & Variable Selection
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