Introduction to foundational concepts, theories, and techniques of statistical analysis for data science. Students will begin with descriptive statistics and probability, and advance through multiple and logistic regression. Will explore in greater depth linear and logistic regression, and continue additional regression and classification techniques with a focus on application. Analyses will be completed in R. Practical issues in data analysis and graphics such as programming in R, debugging R code, Jupyter Notebook, cloud computing, data exploration, and data visualization.
PRQ: None