Stats Central - Online Short Course: Intro to Stats for Researchers, May 11-14 2020


Note: The course should be attended remotely, and will be delivered using online collaborative teaching tools, as a mix of live video-assisted lectures and computer-based tutorials, with a chat session and multiple support staff to answer questions.

Course Overview

In many disciplines, researchers wishing to publish are asked to provide a rigorous statistical analysis. Reviewers are often specific about what statistical measures they want included. "Why wasn't Fisher's Exact Test used?" "Was an appropriate sample size determined a priori?"

Statistical analyses require specialised software to perform calculations. In this course, we use the free statistical program R, although researchers may have another statistical package available to them.

How does one decide which statistical procedure is the most appropriate? What do all the sections of the output mean?

This course 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. This course is designed to help you, the researcher. It is helpful if you have done an undergraduate statistics subject, although this course can serve as a first introduction or a refresher.

Instructions on how to carry out particular statistical analyses will be provided, with an emphasis on interpreting the computer output (most packages produce similar output). There will be plenty of practical work throughout the course.

Do you need to have previous experience using the program R?

It would be very helpful if you have some basic knowledge of R. We recommend our one-day course, Introduction to R, which runs just prior to this course. However, previous experience with statistical packages like SAS, SPSS or Stata or some basic programming skills are also helpful.

In this course, the statistical software package used is R exclusively. We do not use or demonstrate SPSS.

Course Outline

This course will cover topics including:


Types of experiments, scales of measurement, which method to use.

Summarising and Graphing Data

Ways of presenting data (histograms, boxplots), measures of centre and spread, analysing tables, correlation, and confidence intervals.

Comparing Groups

Hypothesis testing concepts - power, significance, P-value. Comparing two groups (t-tests, Wilcoxon).

Comparing many groups (with one treatment factor) - one-way ANOVA or Kruskal-Wallis - multiple comparison tests.

Finding Relationships

Correlation, predicting relationships (regression - simple).

Other topics covered

Non-Normal data - transformations and non-parametric tests. If time is available, we will briefly discuss sample size and power.


Course Requirement: You will need a computer with access to the course.

Duration: 9.00am to 1.00pm - each day

Location: Online


Online Course Fees (heavily discounted rates with 50% off standard fees)

UNSW Student: $100

UNSW Staff: $200

External Student: $375

External: $500

You will receive a certificate of completion for the course.