Practical Statistics for Data Scientists Using R

Get a hands-on introduction to statistics for data science using the R programming language. You explore the foundations of statistics with a strong emphasis on constructing models from data. Topics include descriptive statistics, probability (including conditional probabilities and Bayes rule), multiple regression, multiway analysis of variance, and logistic regression. You also study statistical concepts, methods, tools for modeling multivariate systems, and the statistical foundations for machine and statistical learning applications for drawing reliable conclusions from real-world data. You also get a basic introduction to the R programming language and R tools for data exploration, modeling and presentation of results.