NOTES: In the equation, betas are unknown and X is observed to predict Y (known as predictors) Hyperplane is a plane that tries to minimize the squared distance between the points when you have multiple predictors p-values close to 1 are not significant completed 08.08.2024
2:14 should it be not the closest point to the plane? As the closest point to the plane is the perpendicular projection onto the place but not f(x1, x2) in R^3
The distance between a data point and its projection vertically to the plane along the vertical axis might be more easily interpreted. However, regression can also be solved using least-squares I think (which is in the sense of orthogonal projection you just mentioned).
I think you're right; it should be the perpendicular projection, and I think the presenter probably just misspoke or didn't realize what he said wasn't accurate.
Hi, thanks for the info, but where are the codes? Without codes or the real examples of the statics in Python, it is just a dry class or session. Please, can we be like Karl Pearson? I am sorry to say it in a not very positive way. Thanks again.
Multiple linear regression? More like "Magnificent lectures to which you should listen". 👍
NOTES:
In the equation, betas are unknown and X is observed to predict Y (known as predictors)
Hyperplane is a plane that tries to minimize the squared distance between the points when you have multiple predictors
p-values close to 1 are not significant
completed 08.08.2024
Thank you sir
2:14 should it be not the closest point to the plane? As the closest point to the plane is the perpendicular projection onto the place but not f(x1, x2) in R^3
The distance between a data point and its projection vertically to the plane along the vertical axis might be more easily interpreted.
However, regression can also be solved using least-squares I think (which is in the sense of orthogonal projection you just mentioned).
I think you're right; it should be the perpendicular projection, and I think the presenter probably just misspoke or didn't realize what he said wasn't accurate.
Hi, thanks for the info, but where are the codes? Without codes or the real examples of the statics in Python, it is just a dry class or session. Please, can we be like Karl Pearson? I am sorry to say it in a not very positive way. Thanks again.