Wednesday 8th November 2023

Target Audience

This one day on-line course is aimed at complete beginners to acquire the skill necessary to use SPSS files.

The course tutor, Elizabeth Wiredu, is a Medical Statistician. Elizabeth has 29 years of experience, providing teaching and learning support for graduate schools, postgraduate students, medical doctors and other health researchers. She has served as an in-house medical statistician at University Hospitals of Aintree and trained doctors in Mersey Deanery on medical statistics. Elizabeth was a third-party trainer for IBM SPSS UK, delivering their public courses on Statistical Methods for Healthcare professionals.  (https://uk.linkedin.com/in/elizabethwiredu)

A booking form is at https://assess-spss.co.uk/workshop-form/

Pre-requisites 

This workshop is suitable for users who have no prior experience using SPSS.

Aim

This one-day course will provide you with a thorough and practical understanding of Correlation: Simple and Multiple Linear Regression, and Logistic Regression. You will be guided on how to generate Pearson’s correlation coefficient, Spearman’s rho, and Kendall’s tau-b and explain the results. You will gain knowledge and competence that will enable you to graphically screen your data for linear relationship before generating correlation coefficient and then follow it with regression analysis. Health and medical examples are used to enhance understanding of the concepts of correction and regression within health context.

Learning Outcomes

By the end of the course, you will be able to:

Correlation
• Explore linear relationship between two variables using simple scatter plots.
• Measure relationship between two variables using correlation coefficient.
• Understand parametric (Pearson) and non-parametric (Spearman, Kendall’s tau) correlation.
• Examine partial correlation for confounding effect.

Regression
• Understand the concept of linear regression.
• Perform Simple and Multiple Linear Regressions.
• Perform Binary Logistic Regression.
• Assess the goodness of fit of regression model.
• Interpret regression model and write the regression equation.