Course on Data Management, Analysis and Graphics with R

Who should attend?

• • Statisticians & Researchers
  • Planners & Monitors and Evaluators
  • NGOS & Government Ministries
  • Project Managers

  Learning Objectives

  • • The participants will learn ways of effectively handling data and how to use R as a storage facility.
    • The participants will learn how to use R as a suite of operators for calculations on arrays, in particular matrices.
    • The participants will learn how to use R for large, coherent, integrated collection of intermediate tools for data analysis
    • The participants will learn how to use R graphical facilities for data analysis and display either on-screen or on hardcopy
    • The participants will learn how to use R for well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.

  Course Content

  Introduction to R

  • Why use R?
  • Obtaining and installing R
  • The R environment
  • Working with R
  • Packages
  • The available help
  • Batch processing
  • Using output as input—reusing results
  • Working with large datasets
  • The R workspace, managing objects
  • R Packages
  • Conflicting objects
  • Editors for R scripts

  Data Objects (Data types and Data structures)
  Data types

  • Double
  • Integer
  • Complex
  • Logical
  • Character
  • Factor
  • Dates and Times
  • Missing data and Infinite values.

  Data structures

  • Vectors
  • Matrices
  • Arrays
  • Data frames
  • Time-series objects
  • Lists
  • The string function

  Importing data

  • Text files
  • Excel files
  • Databases
  • From other statistical software

  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
  • Sub setting datasets
  • Using SQL statements to manipulate data frames

  Introduction to R Graphics

  • Introduction
  • High-level plotting commands
  • Low-level plotting commands
  • Interacting with graphics
  • Modifying a graph

  Working with Graphics in R

  • Graphs and charts for dichotomous and categorical variables
  • Graphs and charts for ordinal variables
  • Tabulations for summary statistics for continuous variables
  • Graphs and charts for continuous variables

  Summarizing data using R

  • Numerical summaries for discrete variables
  • Tables for dichotomous variables
  • Tables for categorical variables
  • Tables for ordinal variables

  Quantitative data Analysis using R

  • Planning for qualitative data analysis
  • Basics for statistical analysis
  • Testing for normality of data
  • Choosing the correct statistical test
  • Hypothesis testing
  • Confidence intervals
  • Tests of statistical significance (Parametric and non-parametric tests)
  • Hypothesis testing versus confidence intervals

  • For further inquiries, please contact us on 

    Tel: +254 20 2000 957.

    Mob: +254 727 446 544.

    Email: info@ajtraining.co.za

    REQUIREMENTS AND TRAINING VENUE

    The training is residential and will be held at AJT Training Centre. Delegates should be reasonably proficient in English. Applicants must live up to Alexander James Training (AJT) admission criteria.

    ACCREDITATION

    Upon successful completion of this training, participants will be issued with an Alexander James Training (AJT) certificate.

  • CUSTOMIZED/TAILOR- MADE

    We will customize this training to fit your professional and institution expected outcome. You can have it delivered in our AJT Training Centre or at a convenient location.

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