2021 - 2022: Schedule
Here’s your roadmap for the semester!
- Readings should be completed before each class session
- Class materials (slides, in-class activities, etc.) will be added on the day of class
📝 Course outline: Click here
Week 0: R and RStudio Installation
Welcome you all to STA 517 3.0 Programming and Statistical Computing with R 👏
To participate in the lectures, please bring a laptop with R and RStudio installed.
Week 1: Introduction to R, RStudio and R Programming Basics
Week 2: Data Structures in R (Vector, Matrix, Array, Data Frame, List)
Week 3: Built-in functions in R
Week 4: Writing functions in R
Week 5-1: Control structures
Week 5-2: Introduction to the tidyverse, pipe operator and data import and export
Week 6: Reproducible reporting with R Markdown
🖥️ R Labwork
Rmarkdown_practical_lesson_21.Rmd
sampleimage.png
Output: Rmarkdown_practical_lesson_21.html
Data import and export
Week 7: Mid-Exam
Week 7: Data wrangling with tidyr and dplyr
Reshaping Data
Data Manipulation
Week 8: The grammar of graphics
Week 9: Introduction to statistical modelling
Week 10: Methods of generating random numbers
Week 11: Hypothesis testing
Data Analysis:
Spatial data visualization
Kenya Census: download data
Handling missing values
African Names Database
Data description: here
african_names <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-06-16/african_names.csv")
Week 12: Hypothesis Testing
| Slides |
Reading - Inference Notes |
Cheat sheet |
R-script |
Problems |
Answers |
Week 13: Functional programming with R
Week 14: Bootstrap and Jackknife
Week 15: Recap
