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Codecademy

Learn R

via Codecademy

Overview

R is a popular language used by data scientists and researchers. If you are working with data, R is a fantastic language to learn.

### Why Learn R?
R is a widely used statistical programming language that’s beloved by users in academia and industry. R works well with data, making it a great language for anyone interested in data analysis, data visualization, and data science.
### Take-Away Skills
In this course, you’ll be exposed to fundamental programming concepts in R. After the basics, you’ll learn how to organize, modify and clean data frames, a useful data structure in R. Then you’ll learn how to create data visualizations to showcase insights in data! Finish up with statistics and hypothesis testing to become a data analysis expert.
### Note on Prerequisites:
You do not need to know how to code to enroll in this course!

Syllabus

  • Learn R: Introduction: Learn the basics of R Syntax and jumpstart your journey into data analysis.
    • Lesson: Introduction to R Syntax
    • Project: Calculating Population Change Over Time with R
    • Quiz: Introduction to R
    • VideoContentItem: Introduction to the RStudio IDE
    • VideoContentItem: How is R Special?
  • Learn R: Data Frames: Learn how to organize and modify data in R using data frames and dplyr.
    • Lesson: Introduction to Data Frames in R
    • Lesson: Modifying Data Frames in R
    • Quiz: Manipulating Data Frames in R
    • Project: Explore the 1985 Cars Dataset
  • Learn R: Data Cleaning: Learn how to prepare data for analysis in R using dplyr and tidyr.
    • Lesson: Data Cleaning in R
    • Quiz: Data Cleaning in R
    • Project: Cleaning US Census Data
  • Learn R: Fundamentals of Data Visualization with ggplot2: Learn the basics of how to create visualizations using the popular R package ggplot2.
    • Lesson: Intro to Visualization with R
    • Quiz: Introduction to ggplot2
    • Project: Visualizing Carbon Dioxide Levels
  • Learn R: Aggregates: Learn the basics of aggregate functions in R with dplyr, which let us calculate quantities that describe groups of data.
    • Lesson: Aggregates in R
    • Quiz: Aggregates in R
    • Project: A/B Testing for ShoeFly.com
  • Learn R: Joining Tables: Learn the basics of joining tables together in R with dplyr.
    • Lesson: Joining Tables in R
    • Quiz: Joining Tables in R
    • Project: Page Visits Funnel
  • Learn R: Mean, Median, and Mode: Learn to use R or manually calculate the mean, median, and mode of real-world datasets.

    • Lesson: Mean in R
    • Lesson: Median in R
    • Lesson: Mode in R
    • Project: Central Tendency for Housing Data in R
    • Quiz: Mean, Median, and Mode in R
  • Learn R: Variance and Standard Deviation: In this module, you will learn how to quantify the spread of the dataset by calculating the variance and standard deviation in R.
    • Lesson: Variance in R
    • Lesson: Standard Deviation in R
    • Quiz: Variance and Standard Deviation in R
    • Project: Variance in Weather in R
  • Learn R: Quartiles, Quantiles, and Interquartile Range: In this course, you will learn how to calculate three important descriptive statistics that describe the spread of the data.
    • Lesson: Quartiles
    • Lesson: Quantiles
    • Lesson: Interquartile Range
    • Quiz: Quantiles, Quartiles, and IQR
    • Project: Life Expectancy By Country
  • Learn R: Hypothesis Testing: Learn about the statistics used to run hypothesis tests. Then, learn how to use R to run different t-tests that compare distributions.
    • Lesson: Hypothesis Testing with R
    • Quiz: Hypothesis Testing with R
    • Project: Blood Transfusion Analysis

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