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IBM SPSS Statistics Grad Pack 29.0 BASE DOWNLOAD- Win/Mac – 3 years
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Includes:
- IBM SPSS Base 29
- Bootstapping and Data Preparation modules
- No limitation on the number of variables or cases
- System requirements are at the bottom of this product description
PLEASE NOTE: Will not run on the following:
- Windows Vista
- Windows XP
- Chromebooks
- IPads
- Android tablets
- Smartphones
Be sure you have all the add-ons needed for your course or dissertation! The Base version does not include all add-ons and you may not purchase them separately. Consider the Grad Pack Premium or GradPack Standard
What’s New in IBM SPSS Base 29
- Several new extensions
- New modeling tools
- Workbook mode enhancements
- Search enhancements
Using IBM SPSS Statistics, you can:
- Quickly understand large and complex data sets using advanced statistical procedures, ensuring high accuracy to drive quality decision-making.
- Reveal deeper insights and provide better confidence intervals with visualizations and geographic spatial analysis.
- Process and deploy analytics faster with flexible deployment options.
- Use the Temporal Causal Modeling (TCM) technique to uncover hidden causal relationships among large numbers of time series and automatically determine the best predictors.
- Integrate, explore and model location and time data, and capitalize on new data sourcesÂ
- The Spatio-Temporal Prediction (STP) technique can fit linear models for measurements taken over time at locations in 2D and 3D space.
- The Generalized Spatial Association Rule (GSAR) finds associations between spatial and non-spatial attributes.
- Embed analytics into the enterprise to speed deployment and return on investment.
- Completely redesigned web reports offer more interactivity, functionality and web server support.
- Enhanced categorical principal component analysis (CATPCA) capabilities.
- Bulk load data for faster performance.
- Stata 13 users can import, read and write Stata 9-13 files within SPSS Statistics.
- Enterprise users can access SPSS Statistics using their identification badges and badge readers.
- A wider range of R programming options enables developers to use a full-featured, integrated R development environment within SPSS Statistics.
With IBM SPSS Statistics Base you can be confident in your analytic results. This comprehensive software solution includes a wide range of procedures and tests to solve your research challenges.
IBM SPSS Base Overview, Features and Benefits
Descriptive Statistics
- Crosstabulations – Counts, percentages, residuals, marginals, tests of independence, test of linear association, measure of linear association, ordinal data measures, nominal by interval measures, measure of agreement, relative risk estimates for case control and cohort studies.
- 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; test linearity; compare via independent sample statistics, paired sample statistics or one-sample t test.
- ANOVA and ANCOVA – Conduct contrast, range and post hoc tests; analyze fixed-effects and random-effects measures; group descriptive statistics; choose your model based on four types of the sum-of-squares procedure; perform lack-of-fit tests; choose balanced or unbalanced design; and analyze covariance with up to 10 methods.
- 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.
Tests to Predict Numerical Outcomes and Identify Groups:
IBM SPSS Statistics Base contains procedures for the projects you are working on now and any new ones to come. You can be confident that you’ll always have the analytic tools you need to get the job done quickly and effectively.
- Factor Analysis – Used to identify the underlying variables, or factors, that explain the pattern of correlations within a set of observed variables. In IBM SPSS Statistics Base, the factor analysis procedure provides a high degree of flexibility, offering:
- Seven methods of factor extraction
- Five methods of rotation, including direct oblimin and promax for nonorthogonal rotations
- Three methods of computing factor scores. Also, scores can be saved as variables for further analysis
- K-means Cluster Analysis – Used to identify relatively homogeneous groups of cases based on selected characteristics, using an algorithm that can handle large numbers of cases but which requires you to specify the number of clusters. Select one of two methods for classifying cases, either updating cluster centers iteratively or classifying only.
- Hierarchical Cluster Analysis – Used to identify relatively homogeneous groups of cases (or variables) based on selected characteristics, using an algorithm that starts with each case in a separate cluster and combines clusters until only one is left. Analyze raw variables or choose from a variety of standardizing transformations. Distance or similarity measures are generated by the Proximities procedure. Statistics are displayed at each stage to help you select the best solution.
- TwoStep Cluster Analysis – Group observations into clusters based on nearness criterion, with either categorical or continuous level data; specify the number of clusters or let the number be chosen automatically.
- Discriminant – Offers a choice of variable selection methods, statistics at each step and in a final summary; output is displayed at each step and/or in final form.
- Linear Regression – Choose from six methods: backwards elimination, forced entry, forced removal, forward entry, forward stepwise selection and R2 change/test of significance; produces numerous descriptive and equation statistics.
- Ordinal regression—PLUM – Choose from seven options to control the iterative algorithm used for estimation, to specify numerical tolerance for checking singularity, and to customize output; five link functions can be used to specify the model.
- Nearest Neighbor analysis – Use for prediction (with a specified outcome) or for classification (with no outcome specified); specify the distance metric used to measure the similarity of cases; and control whether missing values or categorical variables are treated as valid values.
 Please Note:
- Please contact us for technical support or visit the support web site.
- Purchase by anyone other than degree-seeking students is strictly prohibited by the license agreement
- This software includes a 6 month license.
System Requirements:
License Term:Â 6 months
Windows:
Operating system: Microsoft Windows 8, 10 or higher Desktops/laptops only.
Hardware:
Intel® or AMD x86 processor running at 1GHz or higher
Memory: 1GB RAM or more recommended
Minimum free drive space: 800MB***
PLEASE NOTE: Will not run on Windows Vista, XP, Chromebooks, IPads, Android tablets, or smartphones.
Mac:
Operating system: * Apple® Mac 10.13 or higher NOTE: Currently it will not run on Ventura 13.1
- Intel processor
- Memory: 1GB RAM or more recommended
- Minimum free drive space: 800MB***
PLEASE NOTE: Will not run on the following:
- Windows Vista
- Windows XP
- Chromebooks
- IPads
- Android tablets
- Smartphones
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