Fundamental Methods for Data Science in R

Individuals with statistics and programming experience who wish to learn the methods of data science in R.


Expected Duration
137 minutes

R is a free software environment for statistical computing and graphics and has become an important tool in modern data science. In this course, you will learn the fundamental R methods that data scientists use in their everyday work.



  • start the course
  • distinguish data science from statistics and computer science
  • identify some of the problems data scientists solve
  • use various sources of data to learn data science

Important R Basics

  • use data frames to store data in tables in R
  • use the R str function to display the internal structure of data
  • use summary statistics to catch problems before data analysis in R
  • use the rjson R package to import json formatted files
  • use the foreach loop in R

Data Management

  • reshape values in your data in R
  • join data frames using the merge function in R
  • use the transpose function “”t”” in R
  • aggregate data frames in R
  • perform a fixed value imputation and perform a list wise deletion imputation in R
  • perform an imputation using the impute functions from the Hmisc package in R
  • use the R cut function to turn continuous data into discrete categories

Data Analysis

  • identify the most frequently used functions for data analysis in R
  • fit a linear model using lm function in R
  • computing ANOVA using the aov function in R
  • extract coefficients from a modeling function in R
  • extract the fitted values from a modeling function in R
  • extract the residuals from a modeling function in R
  • calculate the variance-covariance matrix in R
  • calculate a confidence interval in R using confint
  • fit a generalized linear model using the glm function in R
  • use the ggplot2 library to plot models in R
  • compute the t-test in R
  • perform a TukeyHSD test in R
  • use the predict function in R

Time Series

  • create a time series in R
  • use the forecast package in R

Practice: Data Science Fundamentals in R

  • use common statistical methods for data analysis in R





Multi-license discounts available for Annual and Monthly subscriptions.