R, ggplot, and Simple Linear Regression

Name: R, ggplot, and Simple Linear Regression
Rating: 4.6 (3910 reviews)

Begin to use R and ggplot while learning the basics of linear regression

Created byCharles Redmond

Last updated 5/2015

English

What you'll learn

Install R and RStudio
Create vectors and data frames in R
Plot points and lines with ggplot
Access vectors from data frames
Group with ggplot
Plot residual lines with ggplot
Fit a least squares line to a data set
Use a least squares line for prediction

Course content

4 sections • 25 lectures • 2h 13m total length

Introduction2:19
Installing R and RStudio2:57
After this lecture, you should be able to install both R and RStudio on your own computer and start a session in RStudio.
A Tour of RStudio2:06
After this lecture, you will know the functions of the four panels in RStudio.
Vectors in R6:32
After this lecture, you will be able to enter vectors into R, access individual coordinates of vectors, and slice vectors.
Data Frames3:35
After this lecture, you will be able to create a data frame out of several vectors and individually access column vectors of data frames.

Installing ggplot22:52
After this lecture, students will be able to install ggplot2
Plotting a point with ggplot8:31
After this lecture, you will be able to plot a point using ggplot.
Controlling axis properties9:00
After this lecture, you will be able to set limits and number of ticks on your axes.
More with color and shape4:22
After this lecture, you will have more colors and shapes to choose from when defining your points.
Graphing lines with ggplot5:11
After this lecture, you will be able to graph lines with ggplot.
More with lines6:10
After this video, you will be able to graph lines with ggplot using the equation of a line.

Normal populations5:20
After this lecture, you will be able to generate samples from normal populations in R.
Plotting a vertical sample6:11
After this lecture, you will be able to plot a vertical stack of points, with the y-coordinates drawn from a normal population, along with a point which represents the mean of that population.
Plotting several vertical samples8:47
After this lecture, you will be able to plot several vertical stacks of points, with the y-coordinates drawn from normal populations, along with points which represent the means of these populations.
Samples along a line8:59
After this lecture, you will be able to plot vertical samples with means lying on a line.
sapply3:47
After this lecture, you will be able to employ the sapply function in R.
Cloud of points10:04
After this lecture, you will be able to generate a cloud of random points based on a true regression line.

Father and son heights5:42
At the end of this lecture, you will be able to load and plot the father/son height data from the R package UsingR.
Equation of a line2:19
At the end of this lecture, you will be able to find the equation of a line given two points on the line.
Residual visualization12:09
After this lecture, you will understand residuals, and you will be able to group with ggplot.
Sum of squared residuals4:57
After this lecture, given any line and set of points, you will be able to find the sum of squared residuals.
The least squares line5:07
After this lecture, you will be able to find the equation of the least squares line in R.
Prediction3:02
After this lecture, you will be able to use the least squares line for prediction.
Reading in Excel files2:35
After this lecture, you will be able to read in data you have stored in an Excel file.
Course wrap-up1:08
This is a review of what we've covered in the course, and I also mention some important concepts that we have not covered, some that I hope to address in future courses.

Requirements

You will need to install both R and RStudio on your computer. We will, however, cover this in the first lecture.

Description

Data science skills are in much demand today, but it is not just the mathematicians, statisticians, and the computer scientists who can benefit from acquiring them. Data science skills are for everyone!

In this course, I help you to begin using R, one of the most important tools in data science, and the excellent graphics package for R, ggplot2. Along the way, I also show you the basics of simple linear regression.

There are no prerequisites. We begin with installation of R and RStudio, and I introduce R and ggplot skills as they are needed as we progress toward an understanding of linear regression.

Students should be able to complete the course within two weeks, working at an easy pace.

Linear regression is a machine learning technique. I hope to create more courses like this one in the future, teaching machine learning, R, ggplot, dplyr, and programming, all at the same time.

Who this course is for:

This course is for beginners interested in using R.
This course is for beginners interested in learning about the graphics package ggplot2.
This course is for beginners interested in learning some basics of linear regression.
This course is NOT for those with a background in statistics who use R and are familiar with ggplot2.

R, ggplot, and Simple Linear Regression

What you'll learn

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Course content

Getting Started5 lectures • 17min

Working with ggplot6 lectures • 36min

Sampling from populations6 lectures • 43min

Simple Linear Regression in R8 lectures • 37min

Requirements

Description

Who this course is for: