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 to stats.central@unsw.edu.au, then 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 enroll in our Introduction to R course, August 5, that runs ahead of this workshop. You will receive a code to register once ticket purchased.

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.

Course outline

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

Presenter and Expertise: Nancy Briggs, Senior Statistical Consultant, UNSW Stats Central

Date: Tuesday 13 to Thursday 15 August 2024

Duration: 9.30am to 4.00pm - each day

Location: K-C27-G16 - Wallace Wurth G16, we highly encourage you to attend the course in-person, online access is limited.

You will receive a certificate of completion for the course.

NOTE: You will receive email from us closer to the course date regarding the course materials, please ensure you provide a correct email address.

Course fees:

UNSW Student - $150

UNSW Staff - $580

External Student - $865

External - $1,155

**Note: If you have a funding support and would like to pay by "Internal Funding Payment", please contact us stats.central@unsw.edu.au.** Thank you!

FAQs

How can I contact the organiser with any questions?

Please send us an email at: stats.central@unsw.edu.au

Short Course: Introductory Statistics for Researchers Using R

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