IBM SPSS Statistics Premium Grad Pack Ver 23.0 12 Month License for 2 Computers Windows or Mac
R 4,415
or 4 x payments of R1,103.75 with
Availability: Currently in Stock
Delivery: 10-20 working days
IBM SPSS Statistics Premium Grad Pack Ver 23.0 12 Month License for 2 Computers Windows or Mac
Includes Windows and Mac versions
New in version 23: Now you can create heat maps with Monte Carlo simulation, view SPSS Statistics output on multiple smart devices at once, produce presentation-ready output and import Cognos TM1 data for analysis
Includes all of the SPSS add ons: Advanced Statistics, Regression,Custom Tables, Data Preparation, Missing Values, Forecasting, Decision Trees, Direct Marketing, Complex Sampling, Conjoint, Neural Networks, Bootstrapping, Categories
Windows Only: Exact Tests, Visualization Designer, Samplepower
Both Windows and Mac versions included. Includes all add-ons in addition to the full version of SPSS Base. See above for details. Includes these statistical tests: Crosstabulations - Counts, percentages, residuals, marginals, tests of independence, test of linear association, measure of linear association, and much more. Frequencies - Counts, percentages, valid and cumulative percentages; central tendency, dispersion, distribution and percentile values. Descriptives - Central tendency, dispersion, distribution and Z scores. Descriptive ratio statistics - Coefficient of dispersion, coefficient of variation, price-related differential and average absolute deviance. Compare means - Choose whether to use harmonic or geometric means and much more. ANOVA and ANCOVA - Conduct contrast, range and post hoc tests. Correlation - Test for bivariate or partial correlation, or for distances indicating similarity or dissimilarity between measures. Nonparametric tests - Chi-square, Binomial, Runs, one-sample, two independent samples, k-independent samples, two related samples, k-related samples. Explore - Confidence intervals for means; M-estimators; identification of outliers; plotting of findings. K-means Cluster Analysis - Used to identify relatively homogeneous groups of cases based on selected characteristics. Hierarchical Cluster Analysis - Used to identify relatively homogeneous groups of cases. TwoStep Cluster Analysis - Group observations into clusters based on nearness criterion, with either categorical or continuous level data. Discriminant - Offers a choice of variable selection methods. Linear Regression - Choose from six methods. Nearest Neighbor analysis - Use for prediction (with a specified outcome) or for classification (with no outcome specified).