2023
Here’s your roadmap for the semester!
- Readings should be completed before each class session
- Assignments are due by 3:00 PM on the day they are due
- Class materials (slides, in-class activities, etc.) will be added on the day of class
Course outline: click here
Week 1: Introduction to R, RStudio and R Programming Basics
Welcome you all to STA 326 2.0 Programming and Data Analysis with R 👏
About the course and course rules
Week 2-3: Data Structures in R (Vector, Matrix, Array, Data Frame, List)
Week 4: Functions in R
Week 4-5: Writing Functions in R
Week 6-7: The Grammar of Graphics
Perform EDA on palmerpenguins using ggplot2
library(palmerpenguins)
data(package = 'palmerpenguins')
Week 8: Reproducible Reporting with R Markdown
🖥️ R Labwork
Rmarkdown_practical_lesson_21.Rmd
sampleimage.png
Output: Rmarkdown_practical_lesson_21.html
Week 9: Introduction to the Tidyverse Data Science Workflow: Tibble, Factor, Pipe operator
Individual Assignment - 1 (5%) 🎓
Assignment: Individual assignment 1
Go to LMS. Deadline: 19 September 2022
Week 10: Flipped classroom - Physical
Flipped classroom work
Week 11: Data Import and Export - Flipped classroom
Week 12: Data Wrangling: Reshaping Data and Data Manipulation - Physical
Reshaping Data
Data Manipulation
Individual Project (30%) 🎓
Assignment: Individual Project
Week 13: Control structures: Physical
Week 14: Regression Analysis with R: Physical (50%) and Pre-recorded lecture and flipped classroom (50%)
Week 15: Hypothesis Testing: Physical
Revision and Ways to Continue Learning R No Matter What You Choose to be Your Next Step
Happy Learning with R
