R training opportunities

Exploring Chi-square and correlation in R

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.

You'll learn:

• 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 

Tuesday 14 November, 9.30 am to 12.30 pm: Register here.

Traversing t tests in R

The primary goal of this workshop is to familiarise you with basic statistical concepts in R from reading in and manipulating data, checking assumptions, statistical tests and visualisations. This is not an advanced statistics course, but is instead designed to gently introduce you to statistical comparisons and hypothesis testing in R.

You'll learn:

• Read in and manipulate data
• Check assumptions of t tests
• Perform one-sample t tests
• Perform two-sample t tests (Independent-samples, Paired-samples)
• Perform nonparametric t tests (One-sample Wilcoxon Signed Rank test, Independent-samples Mann-Whitney U test)

Prerequisites:

This course assumes familiarity with R and RStudio. You should have a good understanding of R syntax and basic programming concepts. Please consider attending Intersect’s following courses to get up to speed: Learn to Program: R , Data Manipulation and Visualisation in R 

Wednesday 15 November 9.30 am to 12.30 pm: Register here.

Exploring ANOVAs in R

This half-day course covers one and two-way Analyses of Variance (ANOVA) and their non-parametric counterparts in R. To better understand the tests, assumptions and associated concepts, we will be using a dataset containing the Mathematics scores of secondary students. This dataset also includes information regarding their mother’s and father’s jobs and education levels, the number of hours dedicated to study, and time spent commuting to and from school. Lifestyle information about alcohol consumption habits, whether the students have quality relationships with their families and whether they have free time after school is included in this dataset.

You'll learn:

• Basic statistical theory behind ANOVAs
• How to check that the data meets the assumptions
• One-way ANOVA in R and post-hoc analysis
• Two-way ANOVA plus interaction effects and post-hoc analysis
• Non-parametric alternatives to one and two-way ANOVA

Prerequisites:

This course assumes an intermediate level of programming proficiency, plus familiarity with the syntax and functions of the dplyr and ggplot2 packages. Experience navigating the RStudio integrated development environment (IDE) is also required.

If you’re new to programming in R, we strongly recommend you register for the Learn to Program: R , Data Manipulation and Visualisation in R  workshops first.

Thursday 16 November, 9.30 am to 12.30 pm: Register here.