Professional Advanced
Programs.

Technology

4. Statistical Analysis with R Programming

Statistical Analysis with R Programming 1. Course Description The Statistical Analysis with R Programming course is designed to equip learners with strong statistical analysis skills using the R programming language. Participants will learn how to perform data analysis, apply statistical methods, and interpret results effectively. The course combines statistical theory with hands-on R programming, making it ideal for students, researchers, and professionals who work with data-driven decision-making. 2. Course Outlines Chapter 1: Introduction to Statistics and R Programming • Overview of Statistics and Its Applications • Introduction to R and RStudio • Basic R Syntax and Data Types Chapter 2: Data Handling and Manipulation in R • Vectors, Matrices, Data Frames, and Lists • Importing and Exporting Data • Data Cleaning and Preparation Chapter 3: Descriptive Statistics • Measures of Central Tendency • Measures of Dispersion • Data Summarization Techniques Chapter 4: Data Visualization in R • Introduction to Data Visualization • Creating Charts with Base R • Advanced Visualization Using ggplot2 Chapter 5: Probability and Distributions • Basic Probability Concepts • Common Probability Distributions • Sampling Techniques Chapter 6: Inferential Statistics • Hypothesis Testing • Confidence Intervals • t-tests and ANOVA Chapter 7: Regression and Correlation Analysis • Simple and Multiple Linear Regression • Correlation Analysis • Interpreting Statistical Results 3. Who Should Join • Researchers and analysts • Students in statistics or economics • Professionals working with quantitative data

View & enrol