Data Science: Linear Regression from Harvard University (edX)
Data Science: Linear Regression from Harvard University (edX) ranks 5th on the list of best online Linear Regression course. Linear regression is typically used to quantify the relationship between two or more variables. This Linear Regression course from Harvard University will teach you how to use R to implement linear regression and adjust for confounding. This is an excellent course, according to our team, for those who want to learn the most common statistical modeling approaches in data science.
Rafael Irizarry, the instructor, is a top Biostatistics professor at Harvard University. He has over 15 years of experience teaching data analysis and applied statistics to students. You will be able to examine confounding and where extraneous variables affect the relationship between two or more other variables after completing this course.
Highlights:
- A basic level course to understand how to use R to implement linear regression.
- Learn from the best instructor of Data Science from Harvard University.
- Know about how Galton originally developed linear regression.
- Get information regarding when to use linear regression and how to implement it.
- Free to learn without any charges. However, you can upgrade the course for 49$ to access graded assignments and certification on passing the exam.
What you'll learn
- Skip What you'll learn
- How linear regression was originally developed by Galton
- What is confounding and how to detect it
- How to examine the relationships between variables by implementing linear regression in R
Duration: 8 weeks, 1-2 hours/week
Rating: 4.5/5
Enroll here: edx.org/course/data-science-linear-regression
