Thank you for detailed explanation. But, I guess that you should centralized the data in order to get meaningful interpretations, otherwise the intercept terms are meaningless. Weight and age cannot be zero.
Hi-if I have a character variable, named season having 5 sampling dates, I changed the season to factor using as.factor option like what you did, but It showed in regression output NA for all dates and result for this factor? Do you have suggestion?
Thank you so much
You're saving my GPA with my current stats course - much thanks!
Thank you very much! It's all I needed
Great explanation ma'am 👌
Well Explained, Thanks
great explanation
Thank you for detailed explanation. But, I guess that you should centralized the data in order to get meaningful interpretations, otherwise the intercept terms are meaningless. Weight and age cannot be zero.
Thanks a lot for this great explanation!
Very useful
was vry helpful. Have you got any video where u show the graphical ploting of this kind of data.
thank you very ,much.
Excellent!
very clear
Thank you so much.
Thank you.
Please discuss ANOVA topic in this vdo
Hi-if I have a character variable, named season having 5 sampling dates, I changed the season to factor using as.factor option like what you did, but It showed in regression output NA for all dates and result for this factor? Do you have suggestion?
Maam do you also teach MCDM ??
Like dematel ??
So,I have a question, lm function in R can recognizedummy variable automatically?
For this u need to convert that variable in factor first
Mam, does the variables that not significant include to the model?
no..it just increases complexity nothing else. so better not to add insignificant variables
Great ❤😘
Madam if i need help in data interpretation at what email address can i seek help.