Statistical analysis with R

Date: 21 Mar 2024 (Thu) & 28 Mar 2024 (Thu) 

Time: 14:30 - 17:00

Venue: Online via Zoom

Target Audience: All Students

Medium of Instruction: English

**Participants are required to join both sessions (2.5 hrs x 2)

Pre-requisite

• Basic R programming skill
• Interested in statistics

What you will learn

• Understand how to summarize and organize characteristics of a dataset by finding means, medians, standard deviations, frequencies and proportions for variables.
• Understand how to inspect the data graphically and statistically by R plotting functions.
• Understand how to perform t-tests, z-tests, one factor ANOVA and chi-square tests for drawing conclusions based on your data.
• Understand how to examine the association between two variables.
• Coursework will be provided to allow hands-on practice.

Course outline

(Lesson 1)

• Importing data into R from an external file
• Accessing individual variables from an imported data
• Creating categorical variables from an imported data
• Finding means, medians and standard deviations for all the variables in the dataset
  • Finding means and standard deviations for subgroups
• Finding frequencies and proportions for categorical variables
• Inspecting the data graphically and statistically by R plotting functions
  • histogram
  • box plot
  • bar chart
  • scatter plot
• The normal distribution and standard normal distribution

   

(Lesson 2)

• t-tests
  • The one-sample t-test for a mean
  • The independent samples t-test to compare two means
  • The paired samples t-test

• z-tests
  • One-sample z-test for a proportion
  • Two-sample z-test comparing two proportions

• One factor ANOVA

• Chi-square tests

• Examining the association between two measurement variables
  • Scatterplots
  • Correlation