R, ggplot, and Simple Linear Regression

R, ggplot, and Simple Linear Regression, available at Free, has an average rating of 4.68, with 25 lectures, based on 3763 reviews, and has 43511 subscribers.

You will learn about 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 This course is ideal for individuals who are This course is for beginners interested in using R. or This course is for beginners interested in learning about the graphics package ggplot2. or This course is for beginners interested in learning some basics of linear regression. or This course is NOT for those with a background in statistics who use R and are familiar with ggplot2. It is particularly useful for This course is for beginners interested in using R. or This course is for beginners interested in learning about the graphics package ggplot2. or This course is for beginners interested in learning some basics of linear regression. or This course is NOT for those with a background in statistics who use R and are familiar with ggplot2.

Enroll now: R, ggplot, and Simple Linear Regression

Summary

Title: R, ggplot, and Simple Linear Regression

Price: Free

Average Rating: 4.68

Number of Lectures: 25

Number of Published Lectures: 25

Number of Curriculum Items: 25

Number of Published Curriculum Objects: 25

Original Price: Free

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

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.

Target Audiences

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.

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.

Course Curriculum

Chapter 1: Getting Started

Lecture 1: Introduction

Lecture 2: Installing R and RStudio

Lecture 3: A Tour of RStudio

Lecture 4: Vectors in R

Lecture 5: Data Frames

Chapter 2: Working with ggplot

Lecture 1: Installing ggplot2

Lecture 2: Plotting a point with ggplot

Lecture 3: Controlling axis properties

Lecture 4: More with color and shape

Lecture 5: Graphing lines with ggplot

Lecture 6: More with lines

Chapter 3: Sampling from populations

Lecture 1: Normal populations

Lecture 2: Plotting a vertical sample

Lecture 3: Plotting several vertical samples

Lecture 4: Samples along a line

Lecture 5: sapply

Lecture 6: Cloud of points

Chapter 4: Simple Linear Regression in R

Lecture 1: Father and son heights

Lecture 2: Equation of a line

Lecture 3: Residual visualization

Lecture 4: Sum of squared residuals

Lecture 5: The least squares line

Lecture 6: Prediction

Lecture 7: Reading in Excel files

Lecture 8: Course wrap-up

Instructors

Charles Redmond
Professor at Mercyhurst University

Rating Distribution

1 stars: 27 votes
2 stars: 49 votes
3 stars: 343 votes
4 stars: 1331 votes
5 stars: 2013 votes

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