15 - 17 May
Accessibility
The virtual component will be run using Zoom, and closed captions will be activated on request. Slides are in PDF format, exercises are in R markdown, and both will be downloadable in advance. If HTML slides and alt text are needed we will make every effort to provide these, please let us know well in advance. Lectures will be recorded and available for a week following the workshop.
Important Notes - please read
1. Participants must have basic R skills prior to workshop
This is NOT an introductory workshop in using the statistical software package, R. Basic R coding will not be taught. To do this workshop successfully, you must have basic proficiency in using the R package. All examples and exercises used in this workshop are done using R. We want to ensure everyone is able to follow the material, and no participant is disappointed.
- If you have basic R skills, that's excellent, please complete this quick task HERE. Once you have completed this and emailed your results you will be given a code to allow you to register.
- If you do not have basic R skills, but want to do the Introductory Statistics for Researchers workshop, you can enrol in our Introduction to R course that runs ahead of this workshop, May 2- register HERE. Once you have registered, you will be given a code to allow you to register for Introductory Statistics for Researchers.
2. Own computer
You will need to bring and use your own computer during the workshop with both R and RStudio installed. You will also need administrator rights to install further packages needed throughout the workshop.
Course Overview
This workshop is designed as an introduction to statistical analysis for researchers. There is emphasis on understanding the concepts of statistical procedures (with a minimum of mathematics, although some will be discussed) and on interpreting computer output. It is designed to help you, the researcher. It is helpful if you have done an undergraduate statistics subject, although this workshop can serve as a first introduction or a refresher. The theory behind the statistical procedures will, in general, not be discussed.
A range of statistical analyses will be discussed in the workshop, as described in the outline below. We will talk through examples of all analysis types and will demonstrate how to carry them out in R. Equal emphasis will also be put on interpreting the output of these analyses. There will be plenty of practical work.
Content
You will be expected to watch this seminar on study design and statistical principles (samples and populations, confounding, statistical inference) ahead of the workshop.
Revision
- Descriptive statistics – mean, mode, standard deviation, inter-quartile range, correlation
- Data visualisation - boxplot, histogram, scatterplot, bar graph
Introduction to statistical inference
- Uncertainty, confidence intervals, p-values, significance/evidence
- T-test (comparing two groups)
- Checking model assumptions
Analysis of continuous responses with linear models
- Simple linear regression
- ANOVA
- Multiple regression, ANCOVA
Analysis of categorical responses
- Relative risk, odds ratios
- Chi-square test
- Logistic regression
Course Requirements: You will need to bring and use your own computer during the workshop with both R and RStudio installed. You will also need administrator rights to install further packages needed throughout the workshop.
Presenter and Expertise: Luz Palacios-Derflingher, Biostatistician UNSW Stats Central
Date: Monday 15 to Wednesday 17 May
Duration: 9.00am - 3.00pm, each day
Location: This workshop will be delivered in person and online
You will receive a certificate of completion for the course.
