23. Simple Linear Regression Intuition - Step 2

SIMPLE LINEAR REGRESSION 2

To get this best fitting line, you take the each of the points on the line, you square them and you take the sum of the squares
So you got to find the minimum of the sum of the squares
The formula is SUM (y - y^)^2 -> min
So basically what a simple linear regession does is it draws lots and lots of these lines
These trend lines all this is like a simplistic way of imagining the linear regression. and it draws all possible trendlines through the dots and counts the sum of those squares every single time.
It then finds the minimum one so it looks for the minimum sum of squares and finds a line which has the smallest sum of squares possible
And that line will be the best fitting line and that is called the ordinary least squares method.

Last updated 6 years ago

To get this best fitting line, you take the each of the points on the line, you square them and you take the sum of the squares
So you got to find the minimum of the sum of the squares
The formula is SUM (y - y^)^2 -> min
So basically what a simple linear regession does is it draws lots and lots of these lines
These trend lines all this is like a simplistic way of imagining the linear regression. and it draws all possible trendlines through the dots and counts the sum of those squares every single time.
It then finds the minimum one so it looks for the minimum sum of squares and finds a line which has the smallest sum of squares possible
And that line will be the best fitting line and that is called the ordinary least squares method.

Last updated 6 years ago