R210: Exploring Chi-Square and correlation in R

Course duration: half day

This course focuses on the realm of inferential statistics, beginning with correlation and reliability using R.

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:

 

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.

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