MATH132

This course begins by introducing data science with an overview of current trends in data science, the history of R, how to install R, and an introduction to R programming. Data structure concepts include exploring data visualization with numerical and categorical data, data transformation, and importing data. The course continues with exploring data analysis including variation, missing values, covariation, patterns, and models. This course concludes with statistical inferences including linear regression with simple/multiple predictors, confidence intervals, hypothesis testing, inference for single mean/proportion, comparing paired means/proportions, many means with ANOVA and machine learning.