Thank you so much for sharing, sir! I have a question. If the data is still not normally distributed after transformation, what should I do? It would be appreciated if you could answer me. Thank you!
Thank you sir for your valuable lecture. But now I have a question that is.... When I will regression analysis then what data will I consider? Original data or transform data. Please reply.
@@RKVarsity thank you sir for your valuable time for me. I have another question if our data is not normally distributed then we will do transform that data. After transform that data showed data had normally distributed. Now if I will regression analysis then what data will I consider Original (not normally distributed) data or (transform normally distributed) data. Please reply.
If the p-value is less than 0.001 (so the data is non-normally distributed), but the kurtosis and skewness falls between ± 1.0, does it need to be transformed to normal distributed data?
Hello, thank you for this video. My skewness and kurtosis was between -1 and 1 for the square root transformation instead of the log 10 transformation. Can I use the square root transformation for multiple regression?
When we transform the data something like mean and standard deviation is being changed in the new transformed variable , So how we can report the results For example in an article?
If the data is obtained from a questionnaire using 5 level Likert scale and it is not normally distributed, can i do the same steps you explained here?
Very well made tutorial, simple and very informative
sir you re a genius
Thank you so much for sharing, sir!
I have a question. If the data is still not normally distributed after transformation, what should I do?
It would be appreciated if you could answer me. Thank you!
amount spent in NZ does not look normally distributed, it looks positively skewed.
Thank you for the lecture
Thank you so much. It's very helpful.
What about reciprocal?sir!
How do you choose which "method" of transformation you will use. You showed us several.
Thank you sir for your valuable lecture. But now I have a question that is....
When I will regression analysis then what data will I consider?
Original data or transform data. Please reply.
@@RKVarsity thank you sir for your valuable time for me. I have another question if our data is not normally distributed then we will do transform that data. After transform that data showed data had normally distributed. Now if I will regression analysis then what data will I consider Original (not normally distributed) data or (transform normally distributed) data. Please reply.
If the p-value is less than 0.001 (so the data is non-normally distributed), but the kurtosis and skewness falls between ± 1.0, does it need to be transformed to normal distributed data?
Hello, thank you for this video. My skewness and kurtosis was between -1 and 1 for the square root transformation instead of the log 10 transformation. Can I use the square root transformation for multiple regression?
Thank you sir.
The second variable is positively skewed. I don't get why it was not transformed.
Thank you :)
When we transform the data something like mean and standard deviation is being changed in the new transformed variable ,
So how we can report the results For example in an article?
@@RKVarsity I think it's not acceptable in Iran
But thank you anyway🙏
If the data is obtained from a questionnaire using 5 level Likert scale and it is not normally distributed, can i do the same steps you explained here?
I have started already with SEM , so is normalization necessary?
Yes.. Normality is the assumption of sem