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Training Course for Data Management, Analysis and Graphics Using R

Location:
Nairobi Kenya
Start Date:
October 22, 2018
End Date:
October 26, 2018
Time:
9:00am to 5:00pm
183,200.00 NGN

Description

Overview
The training objective of this one week Training in Data Management, Analysis and Graphics with R will impact skills that are of very high demand in data management and analysis. R is an integrated suite of software facilities for data manipulation, calculation and graphical display. R is a programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering,) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.

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.

Email: [email protected]

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.

Organizer

Alexander James Training
Organizer's Phone Number: 
+254 746 194200
Organizer's Email: