This training provides practical, hands-on skills for managing and analyzing data using R, a powerful open-source software. Participants learn how to import, clean, manipulate, and analyze large datasets. The course focuses on data-driven decision-making and prepares you to perform complex statistical tasks efficiently. By the end of the program, you’ll confidently use R for data management, statistical testing, and visualization.

Program Objectives

• Introduce new users to R statistical software
• Empower participants in data management and analysis
• Enhance understanding of data types and appropriate analysis choices
• Improve decision-making through accurate data interpretation
• Design digital data capture tools using CSPro and ODK
• Convert data into various formats
• Perform basic and advanced statistical analyses using R
• Identify and apply correct statistical tests
• Conduct advanced analyses such as GLM, PCA, and Power Analysis

Target Audience

This course is ideal for:

• Data professionals working with large datasets
• Researchers and analysts using R for statistical work
• Big data enthusiasts
• Advanced Excel users seeking to transition to R

Training Period

• Classroom: 5 Days
• Online: 7 Days

Course Outline

Module 1: Basic statistical terms and concepts

• Data quality checks and exploratory analysis
• Descriptive statistics and inferential methods
• Data processing tools including CSPro
• Mobile data collection with ODK

Module 2: Introduction to R.

• Why use R and how to install it
• Basics of R environment and packages
• Batch processing and reusing results
• Managing large datasets

Module 3: Data Entry, Management and Manipulation with R

• Creating and understanding datasets
• Data input and structures
• Annotating and recoding variables
• Managing missing and date values
• Sorting, merging, and sub-setting data
• Using SQL with R data frames

Module 4: Tabulations and Graphics with R.

• Graphing qualitative and quantitative data
• Creating basic and intermediate charts
• Customizing and combining graphics
• Frequency and contingency tables

Module 5: Quantitative Analysis using R.

• Descriptive statistics and correlation
• t-tests and non-parametric tests
• Visualizing group differences
• Regression and ANOVA
• Power analysis

Delivery Method

The course combines theory with practical exercises, case studies, and group work. Participants receive training manuals and reference materials.

Certification

Participants who successfully complete the training will receive a certificate of course completion.

Course Booking

Please use the “book now” or “inquire” buttons on this page to either book your space or make further enquiries.