statsprof - multiple linear regression in excel

[@mariemmouakher457]

thank you so much i wish u were my teacher humour and education always works with me (life saviour)

[@jesuschristo5071]

Super helpful, beyond helpful. I can get through the chapters but they're not as easy to follow through without getting to see it simulated.

[@d20207]

This video cleared me a bunch of doubts I had! I will keep watching your videos. Gracias, Saludos desde Colombia.

[@SystemsProjectEngineer]

Fantastic video. I will try this reverse method.

[@miguelmeza9646]

Good vid my dude

[@yazhini4367]

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!

[@jayashreelaxmekuppuswami8600]

Why did u look at the p value to decide which independent variable is to be thrown out?

[@jesuschristo5071]

He explains it's really great in his other video "Interpretting linear Regression Results"

[@forydas-l5b]

Sir... Share something on Conjoint Analysis

[@albenj401]

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.

[@diviyahkumar2583]

the nearer it is to 1, its better. anything >0.8 is pretty good already