Foundation R

• No prior experience with R is required
• Basic familiarity with programming or data analysis concepts is helpful but not necessary

Audience

• Data analysts and statisticians beginning with R
• Researchers and academics exploring data manipulation and visualization
• Professionals transitioning into data science roles

R is a powerful language and environment for statistical computing and data analysis.

This instructor-led, live training (online or onsite) is aimed at beginner-level professionals who wish to gain a mastery of the fundamentals of R and how to work with data.

By the end of this training, participants will be able to:

• Understand the R programming environment and RStudio interface.
• Import, manipulate, and explore datasets using R commands and packages.
• Perform basic statistical analysis and data summarization.
• Generate visualizations using both base R and ggplot2.
• Manage workspaces, scripts, and packages effectively.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Basic overview of R and R Studio

• R overview
• R Studio Environment Windows
  • Script Editor Window
  • Data Environment
  • Console
  • Plots/Help/Packages

Working with Data

• Introduction to vectors and matrices (data.frame)
• Different types of variables
  • Numeric, Integer, factor etc
  • Changing variable types
  • Importing data using R Studio menu functions
  • Removing variables ls() command
• Creating variables at the console prompt – single, vector, data frame
• Naming vectors and matrices
• Head and tail commands
• Introduction to dim, length and class
• Command line import (reading .csv and tab delimited .txt files)
• Attaching and detaching data (advantages vs data.frame$)
• Merging data using cbind and rbind

Exploratory Data Analysis

• Summarising data
• Summary command on both vectors and data frames
• Sub-setting data using square brackets
  • summarising and creating new variables
• Table and summary commands
• Summary statistic commands
  • Mean
  • Median
  • Standard Deviation
  • Variance
  • Count & frequencies
  • Min & Max,
  • Quartiles
  • Percentiles
  • Correlation

Exporting data

• Write table .txt
• Write to a .csv file

R Workspace

• Concept of Working Directories and Projects (menu driven and code – setwd())

Introduction to R scripts

• Creating R Scripts
• Saving scripts
• Workspace images

Concepts of packages

• Installing packages
• Loading packages into memory

Plotting data (using standard default R plot command and ggplot2 package)

• Bar Charts and Histograms
• Boxplots
• Line charts / time series
• Scatter plots
• Stem and leaf
• Mosaic
• Modifying plots
  • Titles
  • Legends
  • Axis
  • Plot Area
• Exporting a plot to a third party application