Data Analysis 101 with R

Overview

What you'll learn

• Manipulate datasets with dplyr by selecting, filtering, summarizing, and mutating data
• Transform and merge complex datasets using efficient R workflows
• Clean and reshape data with tidyr and handle missing values
• Create clear, informative visualizations with ggplot2
• Apply descriptive and inferential statistical methods in R
• Formulate, conduct, and interpret hypothesis tests
• Communicate findings through appropriate visual and statistical summaries

Skills you'll practise

Statistical InferenceProbability DistributionData ProcessingTidyrData AnalysisDplyrData ManipulationGgplot2R (Programming Language)Workflow Management

Advantages and disadvantages

Some points apply to every course of this kind; see how we rank.

Before you start

Beginner: Coding and Data Algorithms (R, Tidyverse) Intermediate: Data Cleaning and Preprocessing (R, Tidyverse) Beginner: Data Visualization and Reporting (R, Tidyverse) Intermediate: Mathematics and Statistics (R, Tidyverse)