Exploring chi-square and correlation in R

Please register your interest by joining the waitlist using your University email*. Tickets will be allocated to registrants two weeks prior to the course.

* People who register without a University email will not be considered when allocating the tickets. Please make sure that you use a valid email address.

About this course

This hands-on training is designed to familiarise you with the data analysis environment of the R programming. In this session, we will traverse into the realm of inferential statistics, beginning with correlation and reliability. We will present a brief conceptual overview and the R procedures for computing reliability and correlation (Pearson’s r, Spearman’s Rho and Kendall’s tau) in real world datasets.

Learning Outcomes:

• Obtain inferential statistics and assess data normality
• Manipulate data and create graphs
• Perform Chi-Square tests (Goodness of Fit test and Test of Independence)
• Perform correlations on continuous and categorical data (Pearson’s r, Spearman’s Rho and Kendall’s tau)

Prerequisites

This course assumes familiarity with R and RStudio. You should have a good understanding of R syntax and basic programming concepts, as well as familiarity with data manipulation (dplyr) and visualisation (ggplot2 package). Please consider attending Intersect’s following courses to get up to speed:

• Learn to Program: R
• Data Manipulation and Visualisation in R

For more information about prerequisites and this course, please visit the course page on our website.

Target Audience and Expectation

This Introductory training is designed for researchers and students who have had little to no formal training in statistics. The session focuses on the practical implementation; basic conceptual understanding and interpretation of the relevant methods and their corresponding outputs, with little emphasis on theory.

The Intersect approach to training

At Intersect, we deliver hands-on courses that targets the day-to-day software and technology problems that researchers face.

For more information about this course and others, see our course catalogue, or visit Learn.intersect.org.au

For more information about how we allocate tickers and address no-shows, see our training policy.