What You'll Learn
- What is R?
- History and applications of R
- Installing and Configuring R and RStudio
- Basic R Syntax and Data Types
- Vectors, Matrices, and Arrays
- Data Frames and Lists
- Conditional Statements (if-else)
- Loops (for, while)
- Creating and Using Functions in R
- Function Arguments and Scoping
- Data Manipulation with dplyr (filter, select, mutate, arrange)
- Data Tidying with Tidyr (pivot_longer, pivot_wider)
- Joining and Merging Data Frames
- Creating Various Types of Plots (scatter plots, bar plots, line plots, histograms)
- Customizing Plot Aesthetics (colors, labels, themes)
- Creating Interactive Plots
- Descriptive Statistics (mean, median, standard deviation, quartiles)
- Hypothesis Testing (t-tests, chi-squared tests)
- Regression Analysis (linear regression, multiple regression)
Requirements
- No R programming experience needed
Who This Course is For
- Anyone who wants to build a strong portfolio of R data projects
- Students in statistics, economics, or data science
- Beginners who want to learn R by doing, not just watching
- Data analysts and professionals transitioning into R from Excel or Python
Your Instructor
Brighter Futures Hub
Instructor at Udemy
4.0 Instructor Rating
721 Reviews
48,968 Students
32 Courses
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