Inferential Statistics for Data Science

4.0 credits

Fundamental concepts in probability and statistics from a data science perspective; rigorous probabilistic reasoning and problem-solving; statistical methods used in data science. Topics to be covered include data exploration through descriptive statistics (with an emphasis on using R for such analyses), random variables, statistical inference, and statistical modeling. The inference portion of the course will focus on building and applying hypothesis tests and confidence intervals for population means, proportions, variances, and correlations. Non-parametric alternatives will also be introduced. The modeling portion of the course will include ANOVA, and simple and multiple regression and their respective computational methods.