Overview
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Get up and running with SPSS Statistics. Learn how to work with the program to make data visualizations, calculate descriptive statistics, and more.
Syllabus
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Introduction
- Welcome
- Using the exercise files
- SPSS in context
- Versions, releases, licenses, and interfaces
- Navigating SPSS
- Sample datasets
- Data types, measures, and roles
- Options and preferences
- Extending SPSS
- Saving and running syntax files
- Visualizing data with Chart Builder
- Modifying Chart Builder visualizations
- Visualizing data with Graphboard templates
- Modifying Graphboard visualizations
- Using legacy dialogs: Boxplots for multiple variables
- Creating regression variable plots
- Comparing subgroups
- Importing data
- Variable labels
- Value labels
- Splitting files
- Selecting cases and subgroups
- Recoding variables
- Reversing values with syntax
- Recoding by ranking cases
- Creating dummy variables
- Recoding with Visual Binning
- Recoding with Optimal Binning
- Preparing data for modeling
- Computing scores
- Computing frequencies
- Computing descriptives
- Exploratory data analysis
- Computing correlations
- Computing contingency tables
- Factor analysis and principal component analysis
- Reliability analysis
- Hierarchical clustering
- k-means clustering
- k-nearest neighbors classification
- Decision tree classification in SPSS
- Neural networks in SPSS: Multilayer perceptron classification
- Neural networks in SPSS: Radial basis function classification
- Comparing proportions
- Comparing one mean to a population: One-sample t-test
- Comparing paired means: Paired-samples t-test
- Comparing two means: Independent-samples t-test
- Comparing multiple means: One-way ANOVA
- Comparing means with two categorical variables: ANOVA
- Computing a linear regression
- Variable selection
- Logistic regression
- Automatic linear modeling
- Exporting charts and tables
- Web reports
- Next steps
