R Statistics
📊 R Statistics
R is widely used in research, economics, healthcare, and data science because of its strong statistical capabilities.
1. Descriptive Statistics (Most Used)
These describe the basic features of data.
| Function | Purpose |
|---|---|
mean(x) | Average |
median(x) | Middle value |
sum(x) | Total |
min(x) | Minimum |
max(x) | Maximum |
range(x) | Min & Max |
length(x) | Number of elements |
2. Summary of Data
✔ Gives Min, 1st Qu., Median, Mean, 3rd Qu., Max
3. Measures of Dispersion (Spread)
✔ Shows how spread out the data is
4. Quantiles & Percentiles
5. Handling Missing Values (NA)
6. Statistical Functions on Data Frames
7. Correlation
Measures relationship between two variables.
✔ Value between -1 and 1
8. Covariance
✔ Shows how variables change together
9. Frequency & Tables
10. Basic Statistical Tests (Intro)
t-test
Two-sample t-test
11. Boxplot (Statistical Visualization)
✔ Shows median, quartiles, outliers
12. Random Numbers & Sampling
📌 Summary
R provides powerful statistical functions
Easy handling of missing data
Supports descriptive & inferential statistics
Ideal for data analysis & research
