Past events

Learn to Program: Python

Introductory Statistics Online

This six week online course introduces students to the basics of applied statistics used in disciplines including psychology, biology, medicine, health, engineering, business, sociology and the arts. The three main areas of study are descriptive statistics, probability distributions and statistical inference.

The SPSS statistical computing package is an integral part of the course.

Data Capture and Surveys with REDCap

Basic Statistics with Stata

Learn a simple yet powerful way to design and carry out analyses in Stata.

This workshop introduces statistical concepts in a non-technical way and emphasises their practical application in Stata. Participants will have plenty of opportunities to gain hands-on experience and access in-class support.

Data Entry and Processing in SPSS

Basic Statistics with R

Learn a simple yet powerful way to design and carry out statistical analyses in R - like a real statistician! This two day workshop introduces statistical concepts in a non-technical way and emphasises their practical application in R. The workshop will provide plenty of opportunities to gain hands-on experience and access support from our expert statisticians.

Beyond Basics: Conditionals and Visualisation in Excel

Longitudinal Trials with REDCap

Data Capture and Surveys with REDCap

Longitudinal Trials with REDCap

Learn to Program: Python

Data Capture and Surveys with REDCap

Data Entry and Processing in SPSS

Excel for Researchers

Learn to Program: Python

Longitudinal Trials with REDCap

Data Capture and Surveys with REDCap

Data Manipulation and Visualisation in R

Learn to Program: R

Sample Size Calculation Workshop
Using free software for sample size and statistical power calculations

G*Power is a free statistical software package for power and sample size analysis. It offers point-and-click functionality and covers a wide variety of statistical tests.

The workshop includes concepts of statistical power and relevant statistical tests presented in a non-technical way. Designed to be hands-on, the workshop focuses on the practical application of statistical methods.

Intermediate Statistics with R: Regression Analysis

The thrilling sequel to the extremely popular 'Basic Statistics with R' takes statistics to the next level! Amanda shakes it up in this two day workshop introducing various types of regression models in a non-technical way and demonstrates their practical application in R. The workshop will provide plenty of opportunities to gain hands-on experience and access support from our expert statisticians.

Basic Statistics with Stata

Learn a simple yet powerful way to design and carry out analyses in Stata.

This workshop introduces statistical concepts in a non-technical way and emphasises their practical application in Stata. Participants will have plenty of opportunities to gain hands-on experience and access in-class support.

Data Manipulation and Visualisation in Python

Basic Statistics with R

Learn a simple yet powerful way to design and carry out statistical analyses in R - like a real statistician! This two day workshop introduces statistical concepts in a non-technical way and emphasises their practical application in R. The workshop will provide plenty of opportunities to gain hands-on experience and access support from our expert statisticians.

Introductory Statistics Online

This six week online course introduces students to the basics of applied statistics used in disciplines including psychology, biology, medicine, health, engineering, business, sociology and the arts. The three main areas of study are descriptive statistics, probability distributions and statistical inference.

The SPSS statistical computing package is an integral part of the course.

Longitudinal Trials with REDCap

Data Capture and Surveys with REDCap

Data Entry and Processing in SPSS

Excel for Researchers

Learn to Program: Python

Data Manipulation and Visualisation in R

Longitudinal Trials with REDCap

Data Capture and Surveys with REDCap

Learn to Program: R

Excel for Researchers

Longitudinal Trials with REDCap

Data Capture and Surveys with REDCap

Application of Machine Learning in Agriculture and Livestock Production

An introduction to meta-analysis with applications in R

Longitudinal Trials with REDCap

Data Capture and Surveys with REDCap

Understanding and analysis of proteomic data

Learning sparse log-ratios for high-throughput sequencing data

The causes and consequences of non-normal distributions in parasitology

Excel for Researchers

Genomic prediction with Bayesian methods

Basic Statistics with R

Learn a simple yet powerful way to design and carry out statistical analyses in R - like a real statistician! This two day workshop introduces statistical concepts in a non-technical way and emphasises their practical application in R. The workshop will provide plenty of opportunities to gain hands-on experience and access support from our expert statisticians.

Introductory Statistics Online

This six week online course introduces students to the basics of applied statistics used in disciplines including psychology, biology, medicine, health, engineering, business, sociology and the arts. The three main areas of study are descriptive statistics, probability distributions and statistical inference.

The SPSS statistical computing package is an integral part of the course.

Longitudinal Trials with REDCap

Data Capture and Surveys with REDCap

Constructing experimental design with the edibble R-package

Excel for Researchers

Data Capture and Surveys with REDCap

Databases and SQL

Excel for Researchers

Longitudinal Trials with REDCap

Data Capture and Surveys with REDCap

Learn to Program: R

SPSS 3: Statistical techniques to explore relationships between variables

Learn to Program: Python

Sample Size Calculation Workshop
Using free software for sample size and statistical power calculations

G*Power is a free statistical software package for power and sample size analysis. It offers point-and-click functionality and covers a wide variety of statistical tests.

The workshop includes concepts of statistical power and relevant statistical tests presented in a non-technical way. Designed to be hands-on, the workshop focuses on the practical application of statistical methods.

SPSS 2: Introduction to statistical techniques to compare groups

Data Manipulation and Visualisation in R

SPSS: Introduction

Learn to Program: R

Excel for Researchers

Data Capture and Surveys with REDCap

Excel for Researchers

Learn to Program: R

Data Manipulation and Visualisation in Python

REDCap Community Hour

Learn to Program: Python

Basic Statistics with Stata

Learn a simple yet powerful way to design and carry out analyses in STATA.

This workshop introduces statistical concepts in a non-technical way and emphasises their practical application in STATA. Participants will have plenty of opportunities to gain hands-on experience and access in-class support.

Data Manipulation and Visualisation with R

REDCap Community Hour

Learn to Program: R

REDCap Community Hour

Exploring and Predicting Using Linear Regression

SPSS 3: Statistical techniques to explore relationships between variables

SPSS 2: Introduction to statistical techniques to compare groups

Statistical Comparisons using R

Data Capture and Surveys with REDCap

SPSS: Introduction

Excel for Researchers

Statistical Comparisons using R

Collecting Web Data

Learn to Program: Python

Data Capture and Surveys with REDCap

SPSS 3: Statistical techniques to explore relationships between variables

SPSS 2: Introduction to statistical techniques to compare groups

Learn to Program: MATLAB

SPSS: Introduction

Learn to Program: R

Excel for Researchers

Managing Data Capture and surveys in REDCap

Programming with R

Lab and computational methods to analyse transcriptional regulation

Excel for Researchers

Machine learning for statistical analysis

Programming with MATLAB

Intermediate Statistics with R: Regression Analysis

The thrilling sequel to the extremely popular 'Basic Statistics with R' takes statistics to the next level! Amanda shakes it up in this three half day workshop introducing various types of regression models in a non-technical way and demonstrates their practical application in R. The workshop will provide plenty of opportunities to gain hands-on experience and access support from our expert statisticians.

Managing Data Capture and surveys in REDCap

Power analysis for non-normally distributed traits

Basic Statistics with R

Learn a simple yet powerful way to design and carry out statistical analyses in R - like a real statistician! This three half day workshop introduces statistical concepts in a non-technical way and emphasises their practical application in R. The workshop will provide plenty of opportunities to gain hands-on experience and access support from our expert statisticians.. This course is very popular so book early.

Multivariate analyses

SPSS 3: Statistical techniques to explore relationships between variables

Data Manipulation and Visualization in R

Variant detection and genotype calling using GATK

SPSS 2: Introduction to statistical techniques to compare groups

SPSS: Introduction

Excel for Researchers

Exploring and Predicting Using Linear Regression in R

Data Entry and Processing in SPSS

The heritability of Nematodirus egg counts using a mixture model

Data Entry and Processing in SPSS

Statistical Comparisons using R

Generalised linear models and the analysis of count data

Genomic prediction

SPSS: Introduction

General linear models and the estimation of genetic parameters

Using SQL and Databases

SPSS 2: Intro to statistical techniques to compare groups

Programming with R

Collecting Web Data

SPSS 3: Intro to statistical techniques to explore relationships between variables

Programming with Python

SPSS: Introduction

August 19-21

3 half-day sessions,1-5pm daily

Basic Statistics with R

Learn a simple yet powerful way to design and carry out analyses in R.

This workshop introduces statistical concepts in a non technical way and emphasises their practical application in R. Participants will have plenty of opportunities to gain hands-on experience and access in-class support.

The R package will be used within the user-friendly R-Studio interface.

Data Manipulation and Visualisation with R

Excel for Researchers

Managing Data Capture and surveys in REDCap

Excel for Researchers

SPSS 3: Intro to statistical techniques to explore relationships between variables

Data Manipulation and Visualisation in Python

Introductory Statistics Online

This six week online course introduces students to the basics of applied statistics used in disciplines including psychology, biology, medicine, health, engineering, business, sociology and the arts. The three main areas of study are descriptive statistics, probability distributions and statistical inference.

The SPSS statistical computing package is an integral part of the course.

Programming with Python

Basic Statistics with R

Learn a simple yet powerful way to design and carry out analyses in R.

This workshop introduces statistical concepts in a non technical way and emphasises their practical application in R. Participants will have plenty of opportunities to gain hands-on experience and access in-class support.

The R package will be used within the user-friendly R-Studio interface.

Managing Data Capture and Surveys in REDCap

Sample Size Calculation Workshop
Using free software for sample size and statistical power calculations

G*Power is a free statistical software package for power and sample size analysis. It offers point-and-click functionality and covers a wide variety of statistical tests.

The workshop includes concepts of statistical power and relevant statistical tests presented in a non-technical way. Designed to be hands-on, the workshop focuses on the practical application of statistical methods.

Introduction to Programming using Matlab

Intermediate to Advanced Programming in Python

Intermediate to Advanced Programming in R

Managing Data Capture and surveys in REDCap

Excel Fu for Researchers

Software Carpentry  -  Introduction to R

Excel Fu for Researchers

Managing Data Capture and surveys in REDCap

Using Databases and SQL

Programming with R

SPSS 3: Introduction to statistical techniques to explore relationships between variables

Introduction to Programming with Python

Managing Data Capture and Surveys in REDCap

Basic Statistics with R

Learn a simple yet powerful way to design and carry out analyses in R.

This workshop introduces statistical concepts in a non technical way and emphasises their practical application in R. Participants will have plenty of opportunities to gain hands-on experience and access in-class support.

The R package will be used within the user-friendly R-Studio interface.

SPSS: Introduction

Software Carpentry - Introduction to Programming with R

Excel Fu: Excel for Researchers

Basic Statistics with STATA

Learn a simple yet powerful way to design and carry out analyses in STATA.

This workshop introduces statistical concepts in a non-technical way and emphasises their practical application in STATA. Participants will have plenty of opportunities to gain hands-on experience and access in-class support.

Data Manipulation and Visualisation in Python

Software Carpentry - Introduction to programming with Python

Data Manipulation and Visualisation with R

Software Carpentry - Introduction to R

SPSS 2: Introduction to statistical techniques to compare groups

This SPSS session is for participants who have completed the introductory SPSS 1 session or have equivalent knowledge.

Excel Fu for Researchers

Do you have large amounts of data that is messy, incomplete and contains errors?  During this workshop you will learn how to use Excel to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data.

SPSS: Introduction

This SPSS session is for beginners and introduces the basics of SPSS software and quantitative data analysis.

SPSS 2: Introduction to statistical techniques to compare groups

This SPSS session is for participants who have completed the introductory SPSS 1 session or have equivalent knowledge.

Excel Fu for Researchers

Do you have large amounts of data that is messy, incomplete and contains errors?  During this workshop you will learn how to use Excel to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data.

SPSS: Introduction

This SPSS session is for beginners and introduces the basics of SPSS software and quantitative data analysis.

SPSS: Introduction

This SPSS session is for beginners and introduces the basics of SPSS software and quantitative data analysis.

Introduction to Programming using MATLAB

MATLAB is an incredibly powerful programming environment with a rich set of analysis toolkits optimized for solving engineering and scientific problems.Built-in graphics make it easy to visualize and gain insights from data and a vast library of prebuilt toolboxes lets you get started right away with algorithms essential to your domain.

Software Carpentry - Intro to R

R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers.

R can be challenging to learn, especially for people with limited programming experience. This introductory workshop will help you get started.

Basic Statistics with R

Learn a simple yet powerful way to design and carry out analyses in R.

This workshop introduces statistical concepts in a non technical way and emphasises their practical application in R. Participants will have plenty of opportunities to gain hands-on experience and access in-class support.

The R package will be used within the user-friendly R-Studio interface.

Excel Fu for Researchers

Learn how to use Excel to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data.

G*Power Workshop: Sample size analysis for researchers

G*Power is a free statistical software package for power and sample size analysis. It offers point-and-click functionality and covers a wide variety of statistical tests.

Presented by the Statistics Consultancy Platform, this full day G*Power workshop includes concepts of statistical power and relevant statistical tests presented in a non-technical way. Designed to be hands-on, the workshop focuses on the practical application of statistical methods.

Intermediate to Advanced Programming in Python

Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation (https://software-carpentry.org/)

You will learn: - Advanced programming concepts and techniques in Python.
- Dataframes in Python using the Pandas library.
- Visualisation in Python using the Seaborn and the Matplotlib libraries.
- How to blend code, output and documentation with Jupyter notebooks.

Intermediate to Advanced Programming in R

Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation (https://software-carpentry.org/)

You will learn:

- Advanced programming concepts and techniques in R.
- Dataframe manipulation in R using the dplyr and tidyr packages.
- Visualisation in R using the ggplot2 package.
- Best practices for writing code in R using RStudio.

Excel Fu for Researchers

Data rarely comes in the form you require. Often it is messy and incomplete. And sometimes there's too much of it. In this workshop we'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data.

Managing Data Capture and surveys in REDCap

Would you like to enable secure and reliable data collection forms and manage online surveys? Would your study benefit from web-based data entry? This workshop will introduce you to REDCap, a rapidly evolving web tool developed by researchers for researchers. It features free, unlimited survey distribution functionality and a sophisticated export module with support for all standard statistical programs.

Introduction to GraphPad Prism 7
This training session is an introduction to GraphPad Prism 7, covering the basics required for a researcher to analyse, graph and present your research data.

SPSS 3: Introduction to statistical techniques to explore relationships between variables

This session is for participants who have completed an introductory SPSS session or have equivalent knowledge. Learn how to choose the right statistic, types of statistical analysis available depending on variable types and research questions/objectives, correlation analysis (Pearson coefficient, Spearman), Chi square, partial correlation, standard multiple regression and logistic regression.

SPSS 2: Introduction to statistical techniques to compare groups

This SPSS session is for participants who have completed the introductory SPSS session or have equivalent knowledge. In this session, we will discuss:

• how to choose  the right statistic
• the main types of statistical analysis available depending on variable types and research questions/objectives
• t-tests
• one-way ANOVA
• two-way ANOVA
Some useful statistical terminology such as level of significance, types of error, and the difference between statistical significance and effect size will also be discussed.

Software Carpentry - Introduction to programming with Python

In this live coding workshop you will learn:

• Programming concepts and techniques.
• Basic syntax, control structures and data types in Python.
• How to import powerful libraries that support numerical analysis
  (NumPy) and visualisation (Matplotlib)
• approaches to debugging, testing and defensive programming.
How to blend code, output and documentation with Jupyter
notebooks.

Basic Statistics with R

Learn a simple yet powerful way to design and carry out analyses in R.

This workshop introduces statistical concepts in a non technical way and emphasises their practical application in R. Participants will have plenty of opportunities to gain hands-on experience and access in-class support. The R package will be used within the user-friendly R-Studio interface.

Managing Data Capture and surveys in REDCap

This course will introduce you to REDCap, a rapidly evolving web tool developed by researchers for researchers. REDCap features a high level of security, and a high degree of customizability for your forms and advanced user access control. It also features free, unlimited survey distribution functionality and a sophisticated export module with support for all standard statistical programs.

SPSS: Introduction

This SPSS session is for beginners and introduces the basics of SPSS software and quantitative data analysis. In this hands-on session, participants will learn how to:

• start a new file in SPSS
• create a codebook
• define and create variables
• import data from Excel, clean data and check for errors
• obtain descriptive statistics
• assess data normality
• create graphs
• manipulate and transform variables (e.g. to add total scores of a scale)
check the reliability of a scale.

Software Carpentry - Intro to R

R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem, including the powerful RStudio development environment and the Shiny web application framework. Getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation ( software-carpentry.org).

SPSS 2: Introduction to statistical techniques to compare groups

This SPSS session is for participants who have completed the introductory SPSS session or have equivalent knowledge. In this session, we will discuss:

• how to choose  the right statistic
• the main types of statistical analysis available    depending on variable types and research questions/objectives
• t-tests
• one-way ANOVA
• two-way ANOVA

Some useful statistical terminology such as level of significance, types of error, and the difference between statistical significance and effect size will also be discussed.

SPSS: Introduction

This SPSS session is for beginners and introduces the basics of SPSS software and quantitative data analysis. In this hands-on session, participants will learn how to:

• start a new file in SPSS
• create a codebook
• define and create variables
• import data from Excel, clean data and check for errors
• obtain descriptive statistics
• assess data normality
• create graphs
• manipulate and transform variables (e.g. to add total scores of a scale)
check the reliability of a scale.

Excel Fu for Researchers

Data rarely comes in the form you require. Often it is messy and incomplete. And sometimes there's too much of it. In this workshop we'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data.

Introductory Statistics Online This six week online course introduces students to the basics of applied statistics used in disciplines including psychology, biology, medicine, health, engineering, business, sociology and the arts. The three main areas of study are descriptive statistics, probability distributions and statistical inference.

The SPSS statistical computing package is an integral part of the course.

Intermediate to Advanced Programming in R

R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. Join us for this coding workshop to learn advanced programming concepts and techniques in R, dataframe manipulation using the dplyr and tidyr packages, visualisation using the ggplot2 package and best practices for writing code in RStudio.

Introduction to Programming with Python

In this live coding workshop you will learn:

• Programming concepts and techniques.
• Basic syntax, control structures and data types in Python.
• How to import powerful libraries that support numerical analysis
  (NumPy) and visualisation (Matplotlib)
• approaches to debugging, testing and defensive programming.
How to blend code, output and documentation with Jupyter
notebooks.

Introduction to Programming in R

R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. But getting started with R can be challenging, particularly if you've never programmed before. Join us for this coding workshop to learn programming concepts and techniques; basic syntax, control structures and data types in R; how to load external data into R; ways to visualise data and best practices for writing code in R.

Basic Statistics with R

Learn a simple yet powerful way to design and carry out analyses in R.

This workshop introduces statistical concepts in a non technical way and emphasises their practical application in R. Participants will have plenty of opportunities to gain hands-on experience and access in-class support. The R package will be used within the user-friendly R-Studio interface.

Introduction to Programming with Matlab

MATLAB is a powerful programming environment with a rich set of analysis toolkits. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation ( software-carpentry.org).

SPSS 3: Introduction to statistical techniques to explore relationships between variables

This session is for participants who have completed an introductory SPSS session or have equivalent knowledge. Learn how to choose the right statistic, types of statistical analysis available depending on variable types and research questions/objectives, correlation analysis (Pearson coefficient, Spearman), Chi square, partial correlation, standard multiple regression and logistic regression.

Excel Fu for Researchers

Data rarely comes in the form you require. Often it is messy and incomplete. And sometimes there's too much of it. In this workshop we'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data.

SPSS 2: Introduction to Statistical Techniques to Compare Groups

This SPSS session introduces participants to statistical techniques to compare groups, including t-tests, ANOVA and MANOVA. It is designed for those who have completed the introductory SPSS session or have equivalent knowledge.

SPSS 1: Introduction

This SPSS session introduces participants to SPSS software, types of variables, creating a data file, descriptive statistics, graphs, and checking the reliability of a scale. It is designed for beginners and introduces the basics of SPSS software and quantitative data analysis.

Cleaning and Exploring your data with Open Refine

Do you have messy data from multiple inconsistent sources, or open-responses to questionnaires? Do you want to improve the quality of your data by refining it and using the power of the internet? In this workshop we'll work through the various features of Refine, including importing data, faceting, clustering, and calling remote APIs, by working on a fictional but plausible humanities research project.

SPSS 1: Introduction

This SPSS session introduces participants to SPSS software, types of variables, creating a data file, descriptive statistics, graphs, and checking the reliability of a scale. It is designed for beginners and introduces the basics of SPSS software and quantitative data analysis.

Software Carpentry - Intro to R

R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem, including the powerful RStudio development environment and the Shiny web application framework. Getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation ( software-carpentry.org).

SPSS 2: Introduction to Statistical Techniques to Compare Groups

This SPSS session introduces participants to statistical techniques to compare groups, including t-tests, ANOVA and MANOVA. It is designed for those who have completed the introductory SPSS session or have equivalent knowledge.

Basic Statistics with R

Learn a simple yet powerful way to design and carry out analyses in R in this 1.5 day workshop.

Introduction to Longitudinal and Repeated Measures Data Analyses

Learn how to formulate and evaluate a model and to present results mathematically and graphically in this hands-on workshop.

SPSS 3: Introduction to statistical techniques to explore relationships between variables

This session will introduce participants to techniques that explore relationships between variables, including correlation, partial correlation, standard multiple regression and logistic regression.

SPSS 2: Introduction to Statistical Techniques to Compare Groups

This session will introduce participants to statistical techniques to compare groups, including t-tests, ANOVA and MANOVA.

Introductory Statistics Online

This six week course introduces students to the basics of applied statistics used in disciplines including psychology, biology, medicine, health, engineering, business, sociology and the arts. The three main areas of study are descriptive statistics, probability distributions and statistical inference.

The SPSS statistical computing package is an integral part of the course.

Software Carpentry - Introduction to programming with Python

This one day workshop is aimed at researchers and research students. Participants will learn how to code in the Python programming language, a popular language for scientific computing.

SPSS 1: Introduction

This SPSS session is for beginners and introduces the basics of SPSS software and quantitative data analysis.

Software Carpentry with R

R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers.

R can be challenging to learn, especially for people with limited programming experience. This introductory workshop will help you get started.

June 21

Excel Fu for Researchers

Learn how to use Excel to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data.

Bendigo

Excel Fu for Researchers

Learn how to use Excel to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data.

SPSS 2: Introduction to Statistical Techniques to Compare Groups

This SPSS session is for participants who have completed the introductory SPSS 1 session or have equivalent knowledge.

SPSS 1: Introduction

This SPSS session is for beginners and introduces the basics of SPSS software and quantitative data analysis.

Statistics in research

This 2 day course is a practical, hands-on workshop aimed at novice researchers, research students, teaching/research staff and clinicians with a research interest. Day 1 introduces basic research methods and statistics. Day 2 extends on the methods and statistics covered on the first day.

Participants are encouraged to bring and share their own research or case studies to make this learning relevant.

Software carpentry with R

R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. However, getting started with R can be challenging, particularly if you've never programmed before. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.

Learn programming concepts and techniques; basic syntax, control structures and data types in R; how to load external data into R; ways to visualise data and best practices for writing code in R.