Core statistical techniques in SPSS

This video series provides a guide to some of the most commonly used statistical and analytical procedures, showing how to execute them correctly in SPSS Statistics.

Introduction to linear regression

In classical statistics, linear regression is regarded as the ‘gateway to predictive modelling’. For decades students have been taught about regression from theory to practice simply because it still one of the most versatile and simple ways to understand and predict the effect of key factors on critical outcomes.

Modelling non-linear relationships with SPSS

In this video Jarlath Quinn shows how you can move beyond simple linear regression to model curvilinear relationships using techniques such as variable transformations and quadratic regression before finally exploring how log-log regression can be used to model price elasticity of demand.

TURF analysis with SPSS Statistics

In this video Jarlath Quinn introduces the popular TURF analysis technique and demonstrates how to apply it in IBM SPSS Statistics. TURF analysis is used in many industries to find the optimal sub-group of options from a wider portfolio in order to maximise their appeal to an audience or market.

Affinity analysis made easy

This short video shows how you can perform a simple affinity analysis using IBM SPSS Modeler. Affinity analysis can be used to understand interconnected relationships between key factors. For example, in retail it can be used to perform basket analysis, whereby retailers can identify which products are most commonly purchased together by customers in a single transaction or over a given period time.

Download your free copy of our Understanding Significance Testing white paper
Subscribe to our email newsletter today to receive updates on the latest news, tutorials and events, and get your free copy of our latest white paper.
We respect your privacy. Your information is safe and will never be shared.
Don't miss out. Subscribe today.
×
×
WordPress Popup Plugin
Scroll to Top