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Introduction to Data Management, Statistical Analysis and Graphics With R


This course will help participants learn how to program in R and how to use R for effective data analysis. Participants will also learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code.


Upon successful completion of the course, participants should be able to:

  • Use R to perform descriptive statistics including graphics
  • Perform basic inferential statistical analyses including regression analysis
  • Read and write data files
  • Perform data manipulations (eg, creating new variables, merging data sets)
  • Write and use R script files
  • Use R packages
  • Write and use R functions
  • Perform programming in R including loops.



  • The R System
  • The Look and Feel of R
  • The R Project
  • Important datasets

Starting Up

  • Getting started under Windows
  • Use of an Editor Script Window
  • A typical R Session
  • Further Notational Details
  • On-line Help
  • The Loading or Attaching of Datasets
  • Exercises

An Overview of R

  • The Uses of R
  • R Objects
  • Looping
  • Vectors
  • Data Frames
  • Common Useful Functions
  • Making Tables
  • The Search List
  • More Detailed Information
  • Exercises


  • plot () and allied functions
  • Fine control – Parameter settings
  • Adding points, lines and text
  • Identification and Location on the Figure Region
  • Plots that show the distribution of data values
  • Other Useful Plotting Functions
  • Plotting Mathematical Symbols
  • Guidelines for Graphs
  • Exercises

 Lattice graphics

  • Examples that Present Panels of Scatterplots – Using xyplot()
  • Some further examples of lattice plots
  • An incomplete list of lattice Functions
  • Exercises

Linear (Multiple Regression) Models and Analysis of Variance

  • The Model Formula in Straight Line Regression
  • Regression Objects
  • Model Formulae, and the X Matrix
  • Model Formulae in General
  • Multiple Linear Regression Models
  • Polynomial and Spline Regression
  • Using Factors in R Models
  • Multiple Lines – Different Regression Lines for Different Species
  • aov models (Analysis of Variance)
  • Exercises

 Multivariate and Tree-based Methods

  • Multivariate EDA, and Principal Components Analysis
  • Cluster Analysis
  • Discriminant Analysis
  • Decision Tree models (Tree-based models)
  • Exercises

 R Data Structures

  • Vectors
  • Missing Values
  • Data frames
  • Data Entry Issues
  • Factors and Ordered Factors
  • Ordered Factors
  • Lists
  • Matrices and Arrays
  • Exercises


  • Functions for Confidence Intervals and Tests
  • Matching and Ordering
  • String Functions
  • Application of a Function to the Columns of an Array or Data Frame
  • aggregate() and tapply()
  • Merging Data Frames
  • Dates
  • Writing Functions and other Code
  • Exercises

 GLM, and General Non-linear Models

  • A Taxonomy of Extensions to the Linear Model
  • Logistic Regression
  • glm models (Generalized Linear Regression Modelling)
  • Models that Include Smooth Spline Terms
  • Survival Analysis
  • Non-linear Models
  • Model Summaries
  • Further Elaborations
  • Exercises

Multi-level Models, Repeated Measures and Time Series

  • Multi-Level Models, Including Repeated Measures Models
  • Time Series Models
  • Exercises

Advanced Programming Topics

  • Methods
  • Extracting Arguments to Functions
  • Parsing and Evaluation of Expressions
  • Plotting a mathematical expression
  • Searching R functions for a specified token


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 20th May 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 5 Days
Event Date 27-05-2019
Event End Date 31-05-2019
Cut off date 20-05-2019
Individual Price(Kenyan) KES 69,000
Individual Price (International) EUR 790
Individual Price(International in Dollars) USD 920
Location Nairobi, Kenya
We are no longer accepting registration for this event
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