SPSS and Statistics Courses

The course is aimed at clinical and non-clinical researchers and other health care professionals who would like a basic introduction to using the SPSS statistical software package.

This course offers a practical guide to using SPSS for Windows. Topics covered by this course include:

• data entry
• exploring and summarising data
• manipulating data
• data transformations
• data checking

Format of the course: There will be short demonstrations followed by opportunities to work your way through the course handbook at your own pace. Please note that this is not a course on statistics.

The course is aimed at individuals who are required to interpret and/or conduct basic statistical analyses. The course would be relevant to clinical and non-clinical researchers and other health care professionals.

The course will cover the following topics:

• Issues of study design
• Types of data
• Descriptive statistics
• Probability and distributions
• P-values and hypothesis testing
• Confidence intervals
• Univariate techniques (t-tests, correlation, chi-square tests)

Format of the course: A series of lectures aimed at practical application rather than theoretical formulae. No previous knowledge is assumed.

All three days as a package or individual days

The format of these courses: a mix of lectures and computer practicals using SPSS. This will enable participants to gain experience of the theory and practical application of the statistical techniques, as well as interpretation of the accompanying SPSS output.

A basic knowledge of statistics including p-values, hypothesis testing and simple statistical concepts is assumed for all of the following courses. Prior experience of a statistics package or spreadsheet is desirable, but not essential.

The courses would be relevant to clinical and non-clinical researchers and other health care professionals.

Day 1: Modelling continuous outcomes - linear regression

The aim of this course is to introduce participants to more advanced statistical techniques for measured (continuous/discrete) health outcomes. This will enable participants to gain experience of the theory and practical application of the statistical techniques, as well as interpretation of the accompanying SPSS output.

The course will cover the following topics:

• Analysis of variance
• Linear regression

Day 2: Modelling binary outcomes - logistic regression

The aim of this course is to introduce participants to more advanced statistical techniques for binary and categorical health outcomes. This will enable participants to gain experience of the theory and practical application of the statistical techniques, as well as interpretation of the accompanying SPSS output.

The course will cover the following topics:

• Relative risks, odds ratios, and numbers needed to treat
• Logistic regression

Day 3: Modelling time to event outcomes - survival analysis

Survival analysis (or time-to-event analysis) allows the examination of a relationship between patient information recorded at some origin (e.g. referral to secondary care, disease diagnosis) and a binary outcome that may or may not occur at some later point (e.g. death, recovery, hospital discharge). Some underlying theory will be explained, but only enough to facilitate interpretation of the analysis.

Those with no knowledge of multivariable statistical modelling are strongly encouraged to attend the previous two Intermediate Medical Statistics courses (3 and 4) before attending this course.

The course will cover the following topics:

• Censoring and the hazard function
• Estimating the survivor function using the Kaplan-Meier method
• Comparing groups using the log-rank test
• The Cox proportional hazards model
• Model checking procedures