About this Course
This course is designed to give you an understanding of the core statistical techniques and algorithm implementations that data scientists use to understand data and generate knowledge. Students are asked to apply course techniques to real-world problems using real data, as well as think creatively and critically through issues. By the end of the class, you’ll be able to apply statistical methods to data with well-written production code, as well as interpret and communicate results of such analyses.
- Creating quality code using logging, unit testing and functions
- Probability, distributions and inferential statistics
- Hypothesis testing, outliers and missing data
- Linear, multiple, logistic and other types of regression
- Time series and spatial statistics
- Bayesian and computational statistics