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.
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.
Introduction to linear regression Read More »
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.
Modelling non-linear relationships with SPSS Read More »
The video explores moderation analysis, which enables analysts to identify interaction effects that alter the relationship between a dependent and independent variable.
An introduction to moderation analysis Read More »
This video explores mediation analysis – an analytical approach used to test if a third factor could represent the underlying cause of a relationship between an independent and dependent variable.
An introduction to mediation analysis Read More »
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.
TURF analysis with SPSS Statistics Read More »
In this video Jarlath Quinn explains what cluster analysis is, how it is applied in the real world and how easy it is create your own cluster analysis models in SPSS Statistics.
Cluster Analysis with IBM SPSS Statistics Read More »
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.
Affinity analysis made easy Read More »
