Introduction to R Programming Training Course

Start Date: March 1, 2021

End Date: March 3, 2021

Starts in: 1 Days

Event Location: Nairobi

Training Fees: USD 766.00

Other Dates: January 11, 2021, February 8, 2021, March 1, 2021, April 5, 2021, May 17, 2021, June 14, 2021, July 5, 2021, August 9, 2021, September 6, 2021, October 18, 2021, November 15, 2021, December 6, 2021

See Future Events: Data Science and Analytics,Data Analysis,Data Visualization,Data Science,R Programming



This R Programming training course teaches attendees how to use R programming to explore data from a variety of sources by building inferential models and generating charts, graphs, and other data representations.

After completing this course, students will be able to use R to summarize and graph data, calculate confidence intervals, test hypotheses, assess goodness-of-fit, and perform linear regression.


Participants should be reasonably proficient in English.


3 Days

Learning outcomes

  • To introduce new users into using R statistical software.
  • To empower participants on data management and data analysis.
  • To broaden the knowledge of participants on understanding data types and making correct choices for data analysis.
  • To facilitate participants’ understanding of the types of analysis to conduct on their datasets for results.
  • Understand and appropriately use statistical terms and concepts.
  • Design computer-aided data capture screens using CSPRO.
  • Use mobile phone data collection tool Open Data Kit (ODK) to collect survey data.
  • Convert data into various formats using appropriate software.
  • Perform basic data analysis tasks with R.
  • Perform simple to complex data management tasks using R.
  • Correctly identify the appropriate statistical tests for basic analysis s and perform them using R.
  • Perform Advanced Statistical Analysis such as GLM, PCA, and Power Analysis.

Course outline

Basic statistical terms and concepts

  • Basic data quality checks
  • Basic exploratory data analysis procedures
  • Basic Descriptive Statistics
  • The core functions of inferential statistics
  • Common inferential statistics
  • Concepts and Software for Data Processing
  • Data Processing using Census and Surveys Processing Software (CsPro)
  • Use of Mobile Phones for Data Collection and Processing

Introduction to R

  • Why use R?
  • Obtaining and installing R
  • Working with R
  • Packages
  • Batch processing
  • Using output as input—reusing results
  • Working with large datasets

Data Entry, management, and Manipulation with R

  • Creating a dataset
  • Understanding datasets
  • Data structures
  • Data input
  • Annotating datasets
  • Useful functions for working with data objects
  • Creating new variables
  • Recoding variables
  • Renaming variables
  • Missing values
  • Date values
  • Type conversions
  • Sorting data
  • Merging datasets
  • Subsetting datasets
  • Using SQL statements to manipulate data frames

Tabulations and Graphics with R

  • Graphing Qualitative data
  • Graphing Quantitative data
  • Getting Started R Graphics
  • Working with graphs
  • A simple example
  • Graphical parameters
  • Adding text, customized axes, and legends
  • Combining graphs
  • Basic Graphs (Bar plots Pie charts, Histograms, Kernel density plots, Box plots, Dot plots)
  • Intermediate graphs (Scatter plots, Line charts, Correlograms, Mosaic plots)
  • Frequency and contingency tables

Quantitative Analysis using R

  • Descriptive statistics
  • Correlations
  • t-tests
  • Nonparametric tests of group differences
  • Visualizing group differences
  • Regression
  • Analysis of Variance
  • Power Analysis

Advanced Statistical Analysis

  • Generalized Linear Models
  • Principal components and factor analysis
  • Advanced methods for missing data


The instructor-led training is delivered using a blended learning approach and comprises presentations, guided sessions of practical exercise, web-based tutorials, and group work. Our facilitators are seasoned industry experts with years of experience, working as professionals and trainers in these fields.

All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.


Upon successful completion of this training, participants will be issued with a certificate of participation.

Training venue

The training is residential and will be held at T4D Training Centre in Westlands Nairobi, Kenya. The course fees cover the course tuition, training materials, two break refreshments, lunch, and study visits.

All participants will additionally cater for their travel expenses, visa application, insurance, and other personal expenses.


We can also tailor-make our courses for you. This way, you/your organization will benefit by:

  • Using their own tools during the training
  • Being able to choose areas of interest you wish the trainer to put more emphasis on
  • Taking the course in-house or at a venue of choice
  • Cutting on the cost of transport and accommodation

For further inquiries, please contact us on details below:

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Mobile: +254706909947


Accommodation is arranged upon request. For reservations contact the Training Officer.

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Mobile Number: +254706909947

Training fee

The course fee is KES 45,000.00 or USD 660.00 exclusive of VAT. The course fees cover the course tuition, training materials, two (2) break refreshments, lunch, and study visits. Participants will cater for their travel and accommodation costs.


Payment should be transferred to Tech For Development – T4D account through the bank on or before the course starting date.

Send proof of payment to This email address is being protected from spambots. You need JavaScript enabled to view it.

Cancellation policy

Payment for the course includes a registration fee, which is non-refundable and equals 15% of the total sum of the course fee.

  1. Participants may cancel attendance 14 days or more prior to the training commencement date.
  2. No refunds will be made 14 days or less to the training commencement date. However, participants who are unable to attend may opt to attend a similar training at a later date, or send a substitute participant provided the participation criteria have been met

Please Note: The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure



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