This is a bite-size course to learn R programming for applied statistics. In the CRISP-DM data mining process, applied statistics is at the data understanding stage. This course also covers data processing, which is at the data preparation stage.

Content

1. Getting Started
2. Getting Started 2
3. Getting Started 3
4. Data Mining Process
5. Download Data Set
6. Read Data Set
7. Mode
8. Median
9. Mean
10. Range
11. Range 2
12. Range 3
13. IQR
14. Quantile
15. Population Variance
16. Sample Variance
17. Variance
18. Standard Deviation
19. Normal Distribution
20. Skewness and Kurtosis
21. Summary() and Str()
22. Correlation
23. Covariance
24. Inferential Statistics Tests
25. One-Sample T-Test
26. Two Sample Unpaired T-Test
27. Two Sample Unpaired T-Test (Variance not Equal)
28. Two Sample Paired T-Test
29. Chi-Square Test
30. One Way ANOVA
31. Two Way ANOVA
32. MANOVA
33. Simple Linear Regression
34. Multiple Linear Regression
35. Data Processing: Select Variables
36. Data Processing: Sort Data
37. Data Processing: Filter Data
38. Data Processing: Remove Missing Values and Remove Duplicates