Thank you professor. I have a thing. Second formula of linear regression you restricted xs only qualititive. We know independents variable of regression can be any thing regrardless regression type. Multible linear regression xs can be any thing and also simple linear regression also its x can be anything. Is this Indian statistics 😅😅 😅.
3:56 Wrong, in linear regression the data doesn’t need to be normally distributed but rather the error should be i.i.d normal. This is so unfortunate for Actuarial students to learn key concepts of statistical modeling from such erroneous and poor quality lectures. Hope this is just an exception!
Really good explanation
No one is as good as you. You are extraordinary teacher. God bless you
this lecture was super awesome sir!!!
the lecture was awesome
thank u sir
Perez Jennifer Lee Deborah Perez Richard
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Colby Place
Thank you professor. I have a thing. Second formula of linear regression you restricted xs only qualititive. We know independents variable of regression can be any thing regrardless regression type.
Multible linear regression xs can be any thing and also simple linear regression also its x can be anything. Is this Indian statistics 😅😅 😅.
No this is not “Indian statistics”, but this specific tutor probably does not know statistics.
In GLM why the error term is zero?
Sir what is general linear model?
Lol
3:56 Wrong, in linear regression the data doesn’t need to be normally distributed but rather the error should be i.i.d normal.
This is so unfortunate for Actuarial students to learn key concepts of statistical modeling from such erroneous and poor quality lectures. Hope this is just an exception!