Polynomial Regression, R, and ggplot
Polynomial Regression, R, and ggplot, available at Free, has an average rating of 4.6, with 13 lectures, based on 1283 reviews, and has 27289 subscribers.
You will learn about Write functions in R. Graph functions with ggplot. Fit polynomials to data sets. Fit smoothing splines to data sets. This course is ideal for individuals who are This course is for those looking to learn more about R. or This course is for those looking to learn more about ggplot. or This course is for those looking to understand polynomial regression. It is particularly useful for This course is for those looking to learn more about R. or This course is for those looking to learn more about ggplot. or This course is for those looking to understand polynomial regression.
Enroll now: Polynomial Regression, R, and ggplot
Summary
Title: Polynomial Regression, R, and ggplot
Price: Free
Average Rating: 4.6
Number of Lectures: 13
Number of Published Lectures: 13
Number of Curriculum Items: 13
Number of Published Curriculum Objects: 13
Original Price: Free
Quality Status: approved
Status: Live
What You Will Learn
- Write functions in R.
- Graph functions with ggplot.
- Fit polynomials to data sets.
- Fit smoothing splines to data sets.
Who Should Attend
- This course is for those looking to learn more about R.
- This course is for those looking to learn more about ggplot.
- This course is for those looking to understand polynomial regression.
Target Audiences
- This course is for those looking to learn more about R.
- This course is for those looking to learn more about ggplot.
- This course is for those looking to understand polynomial regression.
This course is a sequel to my course "R, ggplot, and Simple Linear Regression". Here we take on polynomial regression and learn how to fit polynomials to data sets. Along the way, we will learn how to write our own functions in R and how to graph them with ggplot. At the conclusion of the course, we will learn how to fit a smoothing spline to data sets.
At a relaxed pace, it should take about a week to complete the course. You will need to have R and RStudio installed, and it would be best if you have a background in R and ggplot equivalent to what you would get if you viewed my first course mentioned above.
Course Curriculum
Chapter 1: Functions in R
Lecture 1: Introduction
Lecture 2: A Review of Functions
Lecture 3: Creating Functions in R
Lecture 4: Plotting Functions with ggplot
Lecture 5: Polynomials
Chapter 2: Polynomial Regression
Lecture 1: Reading in Our Data
Lecture 2: Fitting a Line
Lecture 3: Plotting Points along the Least-Squares Line
Lecture 4: Visualizing the Residuals
Lecture 5: Best Fitting Polynomial of Degree 2
Lecture 6: Best Fitting Polynomial of Degree 3
Lecture 7: Smoothing Splines
Lecture 8: Course wrap-up
Instructors
-
Charles Redmond
Professor at Mercyhurst University
Rating Distribution
- 1 stars: 2 votes
- 2 stars: 14 votes
- 3 stars: 88 votes
- 4 stars: 442 votes
- 5 stars: 737 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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