Statistics and Data Analysis with R

This course is the third course in a 3-part specialization entitled "Statistics and Applied Data Analysis." The course is meant for those familiar with statistics but unfamiliar with the programming language R. The purpose of this course is to teach learners how to use the popular open-source (and thus, free) integrated development environment RStudio to perform basic and complex statistical calculations. After an introduction to basic calculations, vector, matrices, data frames, and how to import data from common file types (.xlsx, .csv, .txt), learners are taught how to solve probability and counting problems in R, followed by discrete and continuous probability distribution calculations, one-sample hypothesis tests, and two-sample hypothesis tests (comparisons). Finally, participants will learn how to create regression models in R and perform analysis of variance (ANOVA). One of the most beneficial aspect of the course are the programming assignments, which are completed online in the R programming language in Jupyter notebooks

• Use statistical functions in RStudio for discrete and continuous distributions
• Create linear, polynomial, and multilinear regression models and make predictions
• Perform one-sample and two-sample hypothesis tests with confidence intervals

• Basic familiarity with statistical terminology
• Readiness for practical exercises