R- Training Course for Data Management, Analysis and Graphics Using R
Details
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
- 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.
Outline
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
AJT specializes in short Corporate and International Development courses between two days and two weeks in length. At AJT, our primary objective is to help develop the skills of our delegates to enable them to tackle existing challenges and grow within their organizations. Our training courses cover virtually all aspects of development, including Research & Data Management, Monitoring & Evaluation, Project Management, Geospatial Information Systems (GIS), Humanitarian Development, Agriculture & Food Security;Climate Change, Health and Social Care,Law & Governance,Energy & Oil, ICT for Development Technology,Team Building and Advanced Management. We also specialize in training statistical research analysis using STATA, SPSS, R, CSPro, ODK, NVIVO and ArcGIS software’s.Our courses have been designed to provide the very best training for all levels – from basic introduction, to intermediary and advanced level. Our courses are delivered in Kenya, South Africa, Nigeria ,Ethiopia and selected locations.
We Help professionals in all fields to develop in the right areasWith clients coming from the Humanitarian and Non Governmental Organizations (NGOs), as well as from the Public and Private sectors, amongst others, it’s fair to say that we have all the bases covered and indeed, if it’s true enlightenment that professionals are interested in, we’re of the firm opinion that the tailored packages that we are able to offer are pretty much unrivalled. In the genre of development training, we strive to be at the leading edge of things and indeed, when it comes to development and humanitarian courses; we believe that we are able to facilitate the needs of one and all. ...