This is the final module I need to clear before completing my Minor in Statistics. It teaches me some familiar concepts relating to statistical analysis and tests in Python, R and SAS (the only language I wasn’t familiar with).
This course introduces students to the statistical computing and programming, with the main focus on R, Python, and SAS. Students will learn basic computing and programming concepts including scripting, variables, expressions, assignments, control structures, and data structures. On the statistical side, they will learn to load raw data, make numerical and graphical summaries of data, and conduct various estimation and testing procedures. Topics include descriptive statistics, statistical estimation, robust estimation, categorical data analysis, testing hypotheses, ANOVA, regression analysis, performing resampling methods and simulations. Some basic knowledge of R is assumed.
Notes
Lectures
- L1 Introduction to R
- L2 Introduction to Python
- L3 Exploring Quantitative Data
- L4 Exploring Categorical Data
- L5 Robust Statistics
- L6 Introduction to SAS
- L7 Two-sample Hypothesis Tests