Date/Time
Date(s) - 10/03/2020
9:00 am - 5:00 pm

Location
G.1E (SCR), Hodgkin Building
Newcomen St


Course description

This tutorial will explain how to undertake inferential analyses that is appropriate for different data types, including hands-on experience of preforming t-tests, chi-square tests, linear and logistic regression analyses. This will also include variable selection procedures based on univariate plots, and how to check important model diagnostics through scatter plots and histograms. Many of the graphical techniques for these procedures will be based upon those from the previous “Descriptive Statistics in R” BRC tutorial.

It will be assumed attendees have had some exposure to basic statistical inference concepts, such as sampling distributions, confidence intervals, hypothesis tests, p-values and regression techniques, although an overview will be provided. It will also be assumed that attendees have attended the previous two R-related BRC courses, or have had some exposure to R before.

  • Learning objectives

    By the end of the session, participants should be able to:

    • Refresher on concepts of statistical inference – sampling distributions, confidence intervals, and hypothesis tests, p-values and regression techniques
    • Refresher on R and R Studio – loading the data and appropriate packages
    • Performing and interpreting basic inferential test – t-test, chi-square tests
    • Variable selection – plotting univariate scatter diagrams
    • Linear regression models – performing models, understanding and interpreting output
    • Logistic regression models – performing models, understanding and interpreting output
    • Model diagnostics – checking comMonday model assumptions through graphical techniques, possible solutions when assumptions aren’t met.

    About the trainer

    Bola Coker is the Senior Data Manager for Medical Statistics.

 

Share: