Data Analytics Using R
Harness the power of R for statistical analysis, data visualization, and reporting.
Modules
- RStudio & Data Types
- Data Frames, Vectors, and Factors
- Importing Data from CSV, Excel
- Using dplyr for Data Wrangling
- Piping & Filtering
- Group By and Summarize
- T-tests, ANOVA, Correlation
- Regression Analysis
- Chi-Square & Hypothesis Testing
- ggplot2 for Visualizations
- Shiny Dashboards
- Reporting with R Markdown
Ready to start learning?
Why R for Analytics?
- R is built for statistics and visualization.
- Preferred in research, pharma, and academia.
- Packages like ggplot2 and dplyr are industry standards.
- R Markdown helps build reproducible analysis reports.
- Essential for analysts who want statistical depth.