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Introduction to R Programming Training Course


This IRES introduction to 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.


  • 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 appropriate statistical test for basic analysis s and perform them using R.
  • Perform Advanced Statistical Analysis such as GLM, PCA and Power Analysis.


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


Participants should be reasonably proficient in English. Applicants must live up to Indepth Research Services (IRES) admission criteria.


The instructor led trainings are delivered using a blended learning approach and comprises of presentations, guided sessions of practical exercise, web based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional 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 an Indepth Research Servithces (IRES) certificate.


The training is residential and will be held at IRES Training Centre. The course fee covers 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.


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..  

Mob: +254 715 077 817

Tel: 020 211 3814


This training can also be customized for your institution upon request to a minimum of 4 participants. You can have it delivered in our training centre or at a convenient location.

For further inquiries, please contact us on Tel: +254 715 077 817, +254 (020) 211 3814 or mailThis email address is being protected from spambots. You need JavaScript enabled to view it.


Payment should be transferred to IRES account through bank on or before C.O.B 15th July 2019.

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


Payment for the all courses 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.


Event Properties

Event Duration 3 Days
Event Date 22-07-2019
Event End Date 24-07-2019
Cut off date 15-07-2019
Individual Price(Kenyan) KES 46,999
Individual Price (International) EUR 539
Individual Price(International in Dollars) USD 627
Location Nairobi, Kenya
We are no longer accepting registration for this event
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