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Development Programming Languages R

So You Need to Learn R

An introduction to R programming and data analysis for scientists, researchers, and analysts
Rating: 4.8 out of 54.8 (3 ratings)
34 students
Created by Jasper McChesney
Last updated 10/2020
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • How to write R code in scripts and functions
  • Obtain summary statistics, aggregate data, and create statistical models
  • How to work with data: load, transform, aggregate, and graph
  • Basic brogramming concepts like data structures and loops

Course content

14 sections • 59 lectures • 6h 21m total length

  • Preview03:37
  • Preview04:07
  • How to Succeed
    02:33

  • Expressions
    03:39
  • Distance Calculation
    1 question
  • Variables
    05:47
  • Word problem
    1 question
  • Functions
    07:35

  • Scripts
    06:14
  • Creating Functions
    04:19
  • Your First Function
    3 questions
  • Function Evaluation
    08:59
  • Practice With Function Parameters and Evaluation
    3 questions

  • Preview03:19
  • Describing Vectors
    07:18
  • Vector Calculations
    06:57
  • Practice Examining Vectors
    3 questions
  • Indexing Vectors
    09:08
  • Practice indexing
    3 questions
  • Vectors in Functions
    05:54

  • Character Data
    07:34
  • Practice With Character Data
    6 questions
  • Factor Data
    05:49
  • Practice With Factors
    3 questions
  • Logical Tests & Data
    10:13
  • Practice With Logicals
    5 questions
  • Conditionals
    04:37
  • Practice With Conditionals
    2 questions
  • Special Values
    04:18
  • Practice With Special Values
    4 questions
  • Numeric Data
    04:16

  • Summarizing with Math and Logic
    07:27
  • Practice Summarizing Data
    4 questions
  • Advanced Indexing
    08:20
  • Practice With Advanced Indexing
    3 questions
  • Sorting and Re-Ordering
    07:27
  • Practice Sorting
    7 questions
  • Binning Data
    07:57
  • Dealing With NA
    05:20

  • Introduction to Matrices
    08:27
  • Preview04:49
  • Matrix Practice Part 1
    3 questions
  • Matrix Names
    04:28
  • Graphing Matrices
    06:15
  • Matrix Operations
    05:19
  • Matrix Practice Part 2
    5 questions
  • Apply
    12:07
  • Practice on State Data
    8 questions

  • Arrays
    08:03
  • Practice with Arrays
    5 questions
  • Lists
    04:12
  • Brief Practice With Lists
    1 question
  • Splitting Data Into Lists
    08:11
  • Data Frames
    07:09
  • Practice With Data Frames
    2 questions

  • The Activities of Data Analysis
    04:01
  • Loading Data From Flat Files
    10:26
  • Practice Loading Data
    2 questions
  • Loading Multiple Files
    04:36
  • Combining Data
    06:26
  • Preview06:35
  • Practice Combining Data
    2 questions

  • Aggregations
    08:18
  • Aggregation Practice
    4 questions
  • Graphing Data Frames
    02:57
  • Packages
    03:22
  • Graphing With ggformula
    07:03
  • Graphing Data Frame Practice
    4 questions
  • Derived Statistics
    07:25

Requirements

  • Familiarity with basic statistics

Description

So you need to learn R. But you've not a programmer. Don't panic. In this course, I'll take you on a guided tour of introductory R programming, so you can build your R skills from the bottom up.

We'll focus on the main tasks of data analysis: You'll learn how to load data, summarize it, analyze it, model it, and visualize it. You'll learn how to address thorny real-world issues, like handling missing values and loading mis-formatted data files.

You'll also get a solid foundation in programming. If you've dabbled in R but found yourself unable to tackle harder problems, this course will help you get a solid footing to move forward. We'll talk about key programming concepts, like data structures and the flow of control. And you'll practice writing code as we go, tackling problems that progressively challenge you, and build your confidence, on carefully crafted example data sets.

I won't take shortcuts, gloss over details, or just give you easy cut and paste examples. I want you to walk away from this class as a junior programmer in R, able to approach whatever real data problems you face at work, in school, or in your research. I've worked in R almost every day for over a decade, in research and industry, to solve real data problems -- and I want to help you do the same.


This course assumes high-school level algebra and some familiarity with statistics. It's appropriate for someone with limited or no prior programming experience, someone who has dabbled in R but wants a more formal introduction, or someone who has worked with other languages like Python, but wants to add R to their repertoire.


Who this course is for:

  • Researchers and academics with limited programming experience
  • R users who want a more formal introduction to the language
  • Analysts who want to add another tool to their skillset
  • People planning a switch into a data science career

Instructor

Jasper McChesney
Data Analyst, Designer, and Teacher
Jasper McChesney
  • 4.8 Instructor Rating
  • 3 Reviews
  • 34 Students
  • 1 Course

Jasper McChesney is a data professional, with over a dozen years' experience working in analytics, visualization, and information design -- in domains spanning biological science to human resources, to digital advocacy. His data. visualization work has won awards and been featured by various news outlets.

He is also a semi-regular instructor, and has taught introductory programming to students from a wide range of backgrounds (sometimes with LEGO robots). He has a formal training in both the life sciences and the humanities, and enjoys teaching those who don't come from a technical background.

Mr. McChesney's teaching philosophy is to emphasize learning by doing, the repetition of key concepts, and scaffolding new knowledge on old. His lectures are casual, and he avoids talking down to his audience. Past students have said:


"He has a very effective explanation style. I've taken similar classes in the past but never understood as much as I do in this class."

"Jasper was very understanding and kind. He really wanted us to learn R and be able to use it effectively."

"Jasper is an excellent lecturer. His assignments were not exhausting nor impossible. He really has a talent for designing homework problems."


Jasper McChesney currently works as a senior data analyst for a major public university.

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