One of the most important skills for any researcher is the ability to work with “R” programming. R programming language is one of the preferred languages used in statistical modelling all over the world. R programming gives a researcher an edge over others by simplifying the data analysis process and allowing the data to be presented more meaningfully.


After the success of our last workshop and based on the various responses, this course was designed for people with different levels of understanding of the R Programme. Spread out over 15 days with each level having a 5-day duration, one can decide which level you want to start at. This is a wonderful opportunity to be introduced to R, and if already introduced, to hone your skills.


About the speaker:

Mr Chandan Kumar Pandey, Center for Wildlife Sciences (CWS), is a Research Assistant, Analysis and Programming, Centre for Wildlife Studies (CWS). He worked as Research Associate at Adavi Trust and as a Research Assistant at the Centre for Ecological Sciences, the Indian Institute of Sciences. He has a Master’s degree (M.Sc. in biology) from Tata Institute of Fundamental Research, Mumbai and a Bachelor’s degree from Sri Jayachamarajendra College of Engg., MYSORE.


Course overview and program:

BEGINNER LEVEL: It will cover the basics of R programming and simple mathematical calculations using codes. Participants will be introduced to various R working environments such as R IDE, RStudio, and VS-code. Further, the focus will be on the Art of programming, followed by simple data handling and wrangling.

Day 1 (5th October)

  • Introduction of R, R-studio, VS-code, and R-IDE

  • How to set up R

  • Introduction of R scripts

Day 2 (6th October)

  • Art of Programming

  • Concept of variables

  • Object type and class

  • Type of operators

  • Navigate computer using R

Day 3 (7th October)

  • Conditional statements. [ex: if -else]

  • Loops

  • Functions

  • Concept of do not repeat yourself

Day 4 (8th October)

  • Descriptive statics

Day 5 (9th October)

  • Exploratory analysis

  • Linear model using R


Learning outcomes:

  • Read, understand and execute the R scripts.

  • Navigate into your computer using R programming.

  • Read and write data from your computer as well as via the web.

  • Concept of loops, conditional statements, and loops.

  • Concept of variable, object type, and object class.

  • Descriptive statistics and basic inferential statistics.


INTERMEDIATE LEVEL: It will cover the application of R programming for statistical analysis. Participants will be introduced to the concept of the linear model followed by Generalized linear models. Finally, we will be recreating the models presented in the published papers.

Day 1 (12th October)

  • Review of basic of R and tour of RStudio

  • Creating the project and concept of version control

  • Version control using GITHUB integration

Day 2 (13th October)

  • Frequency distribution; Normal Distribution, Binomial distribution, and Poisson distribution

  • Linear model and plotting the difference between groups

Day 3 (14th October)

  • Linear regression models; concept

  • Hands-on example of linear regression with a single predictor

  • Hands-on example of linear regression with multiple predictors

  • Plotting the linear models

Day 4 (15th October)

  • Generalized linear model, concept

  • Hands-on example of GLM; Binomial distribution

  • Hands-on example of GLM; Poisson distribution

Day 5 (16th October)

  • Multiple Linear Regression with Interactions

  • Model selection using AIC

  • Revision and tutorial class. [if time permit]


Learning outcomes:

  • Data cleaning and wrangling using Tidyverse Packages.

  • Linear model with single and multiple variables.

  • Generalized linear models.


ADVANCED LEVEL: It will cover the advanced application of R programming for statistical analysis. Participants will be introduced to the concept of the mixed effect linear with case studies.

Day 1 (19th October)

  • Review of Generalized linear regression model and its limitation

  • Needs for mixed effect models

Day 2 (20th October)

  • Linear mixed effect modelling; concept

  • Linear mixed effect model case study

Day 3 (21st October)

  • Generalized mixed effect model (GLMM); concept

  • GLMM with Binomial dataset

Day 4 (22nd October)

  • GLMM with Poisson dataset; concept

  • Hands-on GLMM with Poisson dataset

Day 5 (23th October)

  • Effect Size in statistics

  • Discussion over P value


Learning outcomes:

  • Data cleaning and wrangling using Tidyverse Packages.

  • A linear mixed model with single and multiple variables.

  • Generalized mixed effect linear models.


The targeted audience and assumed background:

This course is aimed at research scholars and those who plan to do research in the future. This course will also help those who work with statistical data. The Beginners Level is meant to introduce the R programming language to new learners. The Intermediate Level is for those who have already been introduced to R and wish to learn more. The last level, Advanced Level, is for those who already enjoy R and want to know more.


Details of the workshop:

  • Date:

  1. Beginner level: 5th October to 9th October 2022

  2. Intermediate level: 12th October to 16th October 2022

  3. Advanced level: 19th October to 23rd October 2022

  • Time: 06:00 pm - 07:30 pm (IST)

  • Mode: Online

  • Platform: Zoom

  • Participation Fee:

Individual course: INR 1,499/-

Total package fee (Beginner+ Intermediate+ Advanced): INR 4,299/-​​

  • Group discount for the total package (min. 4): INR 4,099/-

  • E-Certificates will be provided to all the participants

  • For any queries contact us at:

If you wish to get a reminder to register for the event!