Quantitative Data Analysis Using R

Apply foundational statistical techniques, analyze quantitative datasets, and visualize data-driven insights using the R programming language. In this course, learners will develop the ability to structure data, compute descriptive statistics, measure variability, evaluate relationships between variables, and present analytical results through clear numerical outputs and visualizations. This course is designed to help learners build practical, job-relevant skills in quantitative analysis using R, one of the most widely used tools for statistical computing and data analysis. Learners will benefit by gaining hands-on experience with real analytical workflows, including project setup, dataset import, dataframe creation, and statistical interpretation. By progressing from basic descriptives to correlation analysis and scatter plot visualization, learners develop a complete analytical mindset rather than isolated technical skills. What makes this course unique is its structured, step-by-step approach that connects statistical concepts directly to R implementation. Each module emphasizes clarity, interpretation, and practical application, making the course suitable for beginners as well as professionals seeking to strengthen their analytical foundations. By the end of the course, learners will be equipped to confidently perform and communicate quantitative analysis using R in academic, business, or research contexts

• Structure datasets and compute descriptive statistics using R
• Analyze relationships between variables using correlation and quantitative methods
• Visualize and communicate data insights using plots and statistical outputs in R

• Basic computer and internet skills
• Ability to read instructions in English and complete short practices