Probability and Inferential 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, in combination with maximising your usage of this powerful tool.  

In this two-hour course, we will introduce attendees to probability and inferential statistics in IBM SPSS Statistics. The course will start with running a statistical test to test the association between two fields in a data set. We will start with examining the data, framing the hypothesis, understanding how hypothesis testing works, setting up the test, and examining/interpreting the output. Once the test is run, we will discuss Type 1 and Type 11 error and issues that arise with both problems.

This course will cover the following topics:

• Sample inferential statistical test
• What is probability?
• When is probability used?
• Making inferences about populations from samples
• Influence of Sample Size
• Hypothesis Testing
• Types of Statistical Errors
• Statistical Significance and Practical Importance
• Consideration of statistical assumptions
• Running an inferential statistical test and interpreting the output

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

Best for: Analysts and researchers interested in reviewing probability, hypothesis testing, statistical errors, statistical significance.