IBM SPSS Statistics Grad Pack Base V22.0 12 Month License for 2 Computers Windows or Mac
- Product Dimensions: 6 x 0.5 x 9 inches
- Shipping Weight: 0.3 ounces
- Includes full version of SPSS Base – Windows and Mac versions included
- Be sure you have all the add-ons needed for your course or dissertation! The Base version does not include any add-ons and you may not purchase them separately or at a later time. Consider the Grad Pack Premium or GradPack Standard.
Both Windows and Mac versions included. Includes these statistical tests:Crosstabulations – Counts, percentages, residuals, marginals, tests ofindependence, test of linear association, measure of linear association, andmuch more. Frequencies – Counts, percentages, valid and cumulativepercentages; central tendency, dispersion, distribution and percentile values.Descriptives – Central tendency, dispersion, distribution and Z scores.Descriptive ratio statistics – Coefficient of dispersion, coefficient ofvariation, price-related differential and average absolute deviance. Comparemeans – Choose whether to use harmonic or geometric means and much more. ANOVAand ANCOVA – Conduct contrast, range and post hoc tests. Correlation – Testfor bivariate or partial correlation, or for distances indicating similarityor dissimilarity between measures. Nonparametric tests – Chi-square, Binomial,Runs, one-sample, two independent samples, k-independent samples, two relatedsamples, k-related samples. Explore – Confidence intervals for means;M-estimators; identification of outliers; plotting of findings. K-meansCluster Analysis – Used to identify relatively homogeneous groups of casesbased on selected characteristics. Hierarchical Cluster Analysis – Used toidentify relatively homogeneous groups of cases. TwoStep Cluster Analysis -Group observations into clusters based on nearness criterion, with eithercategorical or continuous level data. Discriminant – Offers a choice ofvariable selection methods. Linear Regression – Choose from six methods.Nearest Neighbor analysis – Use for prediction (with a specified outcome) orfor classification (with no outcome specified).