Are you ready to transform raw data into meaningful insights using R, one of the most powerful tools for statistical computing and data analysis? Whether you’re a beginner or a professional seeking to sharpen your analytical skills, this course takes you on a step-by-step journey through R programming and applied statistics—from the basics all the way to advanced experimental designs.
This practical, hands-on course is designed especially for learners who want to apply statistics in real-world research, healthcare, business, and academic projects. You’ll not only learn the theory but also see how to implement every concept directly in R and RStudio, gaining the skills to analyze, visualize, and interpret data confidently.
What You’ll Learn:
- Getting Started with R & RStudio
Install, set up, and navigate R and RStudio with ease. Learn the fundamentals of coding in R even if you’ve never programmed before. - Working with Data
Import datasets, clean and explore your data, and summarize findings with descriptive statistics and visualizations. - Regression Analyses
Master simple and multiple linear regression, model comparison (hierarchical regression), and predictor selection techniques. - Handling Collinearity
Detect and deal with collinearity and multicollinearity to improve the reliability of your models. - Hypothesis Testing
Conduct t-tests and one-way ANOVA to compare groups and test statistical hypotheses. - Advanced ANOVA Techniques
Learn planned contrasts, factorial ANOVA, repeated measures, and mixed-design ANOVA for more complex experimental designs.
By the End of This Course:
- You’ll be able to:
- Import and manage data in R.
- Generate descriptive and visual summaries.
- Conduct and interpret regression models.
- Apply and understand t-tests, ANOVAs, and contrasts.
- Handle complex experimental designs with confidence.
Take this course and unlock the full potential of R for your research and career!
