Great Explanation! I watched all your videos w.r.t univariate & multiple linear regression on the same dataset and I too tried doing this. It works fine but i have a question - Why have you removed waterfront, view and grade columns from the dataset? I understand those columns might not be required for the regression analysis but if I keep those columns while doing multiple linear regression, it seems like these 3 columns also impact price a lot. P value is 0 for view and grade as well which is less than 0.05 & 0.01. Could you please explain this? if we assume these columns dont impact price value then their P value should be greater that 0.1 right? Looking forward for your response.. Thanks!
This video cleared me a bunch of doubts I had! I will keep watching your videos. Gracias, Saludos desde Colombia.
Good vid my dude
Great Explanation! I watched all your videos w.r.t univariate & multiple linear regression on the same dataset and I too tried doing this. It works fine but i have a question - Why have you removed waterfront, view and grade columns from the dataset? I understand those columns might not be required for the regression analysis but if I keep those columns while doing multiple linear regression, it seems like these 3 columns also impact price a lot. P value is 0 for view and grade as well which is less than 0.05 & 0.01.
Could you please explain this? if we assume these columns dont impact price value then their P value should be greater that 0.1 right?
Looking forward for your response.. Thanks!
Why did u look at the p value to decide which independent variable is to be thrown out?
Sir... Share something on Conjoint Analysis
When you say "R2 looks good." What should we be looking for? What number is acceptable? I'm not a math guy but I can follow directions.
the nearer it is to 1, its better. anything >0.8 is pretty good already