Course Outline

Introduction to IBM SPSS Statistics

Reading data and defining metadata

Selecting cases for analyses

Transforming variables

Using functions to transform variables

Setting the unit of analysis

Merging data files

Summarizing individual variables

Describing the relationship between variables

Creating presentation-ready tables with Custom Tables

Customising pivot tables

Working with syntax

Controlling the IBM SPSS Statistics environment

Course Outline

Introduction to statistical analysis

Examining individual variables

Test hypotheses about individual variables

Testing on the relationship between categorical variables

Test on the difference between two group means

Test on the difference between more than two group means

Test the relationship between scale variables

Predicting a scale variable: Regression

Introduction to Bayesian statistics

Overview of multivariate procedures

Course Outline

Introduction to advanced statistical analysis

Group variables: Factor Analysis and Principal Components Analysis

Group similar cases: Cluster Analysis

Predict categorical targets with Nearest Neighbour Analysis

Predict categorical targets with Discriminant Analysis

Predict categorical targets with Logistic Regression

Predict categorical targets with Decision Trees

Introduction to Survival Analysis

Introduction to Linear Mixed Models

Introduction to Generalized Linear Models

Course Outline

The Logic of Survey Analysis

Data checking and data validation

Data transformations: create new variables

Testing for Reliability and Validity

Analyzing Categorical Variables

Analyzing Interval Variables

Reporting Survey Results for Categorical and Scale Data

Clustering Respondents

Multivariate Analysis using Regression Techniques

Special Issues: Missing Data

Special Issues: Complex Samples and Sample Weights

Measuring Change over Time with Surveys

Decision Tree Analysis