Examining Variable Relationships in IBM SPSS Statistics

In IBM SPSS Statistics, you can work inside a single, integrated interface to run descriptive statistics, regression, advanced statistics, and machine learning models. You can create publication-ready charts, tables, and decision trees in one tool.

IBM SPSS Statistics is easy to use, provides analysis automation, comprehensive statistical tools, integration with open source, and help at your fingertips. Recent changes have also included a complete visual and statistical overview of data in a new tab within the user interface. 

To improve your experience using IBM SPSS Statistics, the Version 1 SPSS experts provide Statistics training, offering both express and longer courses. Training can also be customised for individual users and groups. Investing in training improves and extends your knowledge of statistical analysis and machine learning methods and maximises your usage of this powerful tool.  

IBM SPSS Statistics is a comprehensive statistical platform. Users can bring data into Statistics, examine it, transform it, and run basic and advanced statistical analyses. Descriptive statistics are powerful summaries of your data, but analysts also want to test hypotheses and examine research questions. In this two-hour course, we will move beyond descriptive statistics to examine variable relationships in IBM SPSS Statistics. The most used statistical tests to test variable relationships will be covered.

This course will cover the following topics:

• A quick review of data types and why they matter
• Type of data and appropriate analysis
• Examining relationships between categorical variables: the chi-square test
• Graphing the chi-square test
• Examining relationships between a categorical factor and numeric target: one-way ANOVA
• Graphing a one-way ANOVA
• Examining relationships between scale variables: Correlation
• Graphing a Correlation

Course attendees will receive sample data files and step-by-step exercises that can be completed following the course.

Best for: Researchers and analysts who want to understand how to examine variables relationships in IBM SPSS Statistics.