Short Course: Introduction to R

Course Overview

R is widely used and extremely powerful statistical software. This course assumes that you have never used R before. You will learn how to obtain and install R, which is open-source software, and RStudio, which is a versatile, user-friendly interface for using R. It is very useful to do this course before our introductory statistics course, Introductory Statistics for Researchers.

This course will cover some basic features of R and lay the groundwork for you to improve your R skills independently. The course is self-paced and focused on developing practical skills.

Course Outline

This course will cover topics including:

• Basics of interacting with R – calculations, saving variables so you can reuse them, data types and structures, organising R code in scripts
• Tidyverse – a basic introduction to tidy R code
• Data – reading in and organising data (from spreadsheets) with dplyr
• Plotting – make beautiful figures with ggplot

Course Requirements: You will need a computer with administrator access (to install R and RStudio software before attending the course).

Date: Tuesday 8 August 2023

Duration: 9.00am - 5.00pm

Hybrid: This course will be delivered in person and online

Or visit https://www.eventbrite.com.au/e/short-course-introduction-to-r-tickets-662756972947

Introductory Statistics for Researchers Using SPSS

Course Overview

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. It 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. The theory behind the statistical procedures will, in general, not be discussed.

A range of statistical analyses will be discussed in the course, as described in the outline below. We will talk through examples of all analysis types and will demonstrate how to carry them out in SPSS. Equal emphasis will also be put on interpreting the output of these analyses. There will be plenty of practical work.

Course outline

Revision

• SPSS basics
• 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
• 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 course.

Date: Monday 14 to Wednesday 16 August 2023

Duration: 9.00am - 3.00pm, each day

Hybrid: This course will be delivered in person and online

Or visit https://www.eventbrite.com.au/e/short-course-introductory-statistics-for-researchers-using-spss-tickets-663408411417

Introductory Statistics for Researchers Using R

Course Overview

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. It 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.

The theory behind the statistical procedures will, in general, not be discussed. A range of statistical analyses will be discussed in the course, 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.

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 course with both R and RStudio installed. You will also need administrator rights to install further packages needed throughout the course.

Date: Wednesday 23 to Friday 25 August 2023

Duration: 9.00am - 3.00pm, each day

Location: This course will be delivered in person and online

Or visit https://www.eventbrite.com.au/e/short-course-introductory-statistics-for-researchers-using-r-tickets-662782469207