Data Management, Analysis and Graphics with R Course

Event: Data Management, Analysis and Graphics with R Course

Venue: Indepth Research Services, Naivasha, Kenya.

Event Date: 23rd -27th October, 2017.

NITA CERTIFIED

INTRODUCTION

In this training you will learn how to use R for effective data management and analysis. The training is job oriented and covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, and organizing and manipulating data. Topics in statistical data analysis will provide working examples.

DURATION

5 days.

COURSE OBJECTIVES

• Understand and appropriately use statistical terms and concepts
• 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
• 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 and perform them using R
• Perform Advanced Statistical Analysis using R

TOPICS TO BE COVERED

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
• Subsetting 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

Tailor-Made Training

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.

How to participate

• Tailors make your course.
• Register individual.
• Register as a group.
• Become one of our partners.
• Purchase software’s
• Frequently asked Questions (FAQ’s)

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For further inquiries, please contact us on Tel: +254 715 077 817, +254 (020) 211 3814, +254 731240802, +254 735331020.

Others Details

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