R Training Agenda

Day 1 – R Fundamentals

8:45

• Introduction

9:15

• R and RStudio installation

• RStudio demo

• Basic R concepts, vocabularies

• R operators

• Data types

• Data structures

12:15 Lunch break

14:00

• Data import and Export

• Packages and functions

• Common functions

Day 2 – Data Preparation for Analysis

8:45

• Recap of day 1 – Q & A

• Explore

• Subset

• Re-structure data

• Combine data

12:15 Lunch break

14:00

• Transform

• Missing Values

• Descriptive statistics

• Useful Packages and functions

Day 3 – Data Visualization

8:45

• Recap of day 2 – Q & A

• Elements of Graphics

• Basic steps of data visualization (ggplot2)

• Univariate data visualization

• Bivariate data visualization

• Faceting

12:15 Lunch break

14:00

• Multivariate data visualization

• Plot styling and labeling

• Correlation visualization

• PCA and biplot

Day 4 – Data Analysis

8:45

• Recap day 3 – Q & A

• Experiment designing

12:15 Lunch break

14:00

• Data analysis

Day 5 – R programming

8:45

• Recap day 4 – Q & A

• Functional programming

• Control structures

• Loops

• Regular expressions

12:15 Lunch break

14:00

• Recap training themes

• Q & A

• Resources for further self-learning