Mohamed R. Abonazel

Aim of Course:

 This course will provide a basic introduction to R, and its use in organizing and exploring data. The emphasis is on understanding and working with fundamental R data structures and we will introduce some basic R programming techniques. Once you've completed this course you'll be able to enter, save, retrieve, manipulate, and summarize data using R; you will also have the proper foundation to build your programming skills in R and take advantage of the full power of R.

SESSION 1: Getting Started with R

• What is statistical programming?
• The R package
• Installation of R
• The R command line
• Function calls, symbols, and assignment
• Packages
• Getting help on R
• Basic features of R
• Calculating with R

SESSION 2: Matrices, Array, Lists, and Data Frames  

• Character vectors
• Operations on the logical vectors
• Creating the matrices and operations on it
  
• Creating the array and operations on it
  
• Creating the lists and operations on it
• Making data frames
• Working with data frames

SESSION 3: Editing and Reading Data from Files

• Data types and data structures
• Editing data in R
• Generating data from any distribution
• Reading a data from a file
• Loading data from other R packages
• Save the data in R

SESSION 4: Exploratory Data Analysis (EDA) and Regression Analysis

• Features of data distributions
• Plotting data
• Descriptive statistics for generated data
• EDA such as: Stem-and-leaf plot, Histogram, and Boxplot
• Estimating linear regression model
• Advanced statistical Models

SESSION 5: Programming in R

• Creating the script file in R
• Run R-code file
• Different types of loops such as: for() and while() loops
• Use if statements in for loops
• Fast loops
• Introduction to Simulation and modeling