Statistics and Data Analysis with R

Coursera MOOC / Non-credit USD 49
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Statistics and Data Analysis with R

About this course

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.

What you'll learn

  • Perform basic and complex statistical calculations using R
  • Work with vectors, matrices, and data frames
  • Import data from various file formats like .csv and .xlsx
  • Conduct hypothesis tests and calculations on probability distributions
  • Create regression models and perform ANOVA

Skills you'll gain

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