What you'll learn

Least Square Regression
Build OLS in Statsmodel
Hypothesis Testing
t test
ANOVA
F Statistics
Degree of Freedom of the Model
Plotting Regression Line above the scatter plot (Fitted Values)
Predicting Results
Answer Question statistically


Requirements

Understanding Statistics
Beginner to Python

Description

In this course, you will learn concepts of linear regression. Starting from

Case Study on Big Mac

Statistical Questions

Least Square Regression

Hypothesis testing: t- test

ANOVA and F-test

Correlation

R Square


You will learn the approaches towards regression with case study. First we start with understanding linear equation and the optimization function value sum of squared errors. With that we find the values of the coefficient and makes least square regression. Then we starts building our linear regression in python.

For the model we build we necessary test like hypothesis testing.

t-test for coefficient significance

ANOVA and F-test for model significance.

And finally, we answer the question statically. Hope we are seeing you inside the course !!!

Who this course is for:

Beginner of Python Developer who want to learn Data Science
Solving question related to linear regression

Homepage: https://www.udemy.com/course/linear-regression-with-case-study-in-python-2020/