Introduction

The growing emphasis on evidence-based decision-making has made statistical programming an essential skill for researchers. This workshop introduces participants to the R programming language for data management, statistical analysis, and professional-quality data visualization. Through practical exercises and real-world datasets, participants will learn how to transform raw data into meaningful insights that support research and policy decisions in the social sciences.

Unique Selling Propositions                     

• · Hands-on training using real social science datasets.
• · No prior programming experience required.
• · Covers both statistical analysis and publication-quality visualizations.
• · Focus on reproducible research using R and RStudio.
• · Practical applications for theses, dissertations, and research publications.

Objectives and Learning Outcomes

By the end of the workshop, participants will be able to:

1. Import, clean, and manage social science datasets using R.
2. Perform descriptive and inferential statistical analyses in R.
3. Create professional and publication-ready data visualizations using ggplot2.
4. Interpret statistical outputs and communicate findings effectively.
5. Apply reproducible research practices for academic projects.

Key Topics / Related Concepts

1. Introduction to R and RStudio
2. Data Import, Cleaning, and Manipulation (tidyverse)
3. Descriptive Statistics and Data Exploration
4. Hypothesis Testing (t-tests, ANOVA, Correlation)
5. Linear Regression Analysis
6. Data Visualization using ggplot2
7. Exporting Results and Reproducible Reporting

Activities and Learning Strategies

1. Interactive lectures with live demonstrations.
2. Hands-on coding exercises using real-world datasets.
3. Individual and group practice sessions.
4. Mini case studies from social science research.
5.  Question-and-answer sessions and guided troubleshooting.

Venue / Facilities 

UMT Main Campus; List down required facilities

UMT Main Campus

Required Facilities:

• Computer lab with R and RStudio installed
• Multimedia projector and sound system
• High-speed internet connection
• Whiteboard and markers
• Power outlets for participants' laptops