Statistical Analysis using R


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.


Course Program:

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

Dr. Mohamed Reda Abonazel

Institute of Statistical Studies and Research, Cairo University

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