Checking if error in data is normally distributed or not

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amberly hadden
amberly hadden 2016-4-11
评论： Star Strider 2016-4-11
I have two datasets (x) and (y). How could I know if the error in both data is normally distributed or not? Thank you, Amb

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Star Strider
Star Strider 2016-4-11
One option is the Anderson-Darling test. See the documentation for the adtest function for details. Tare links to others in and at the end of that page.
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amberly hadden
amberly hadden 2016-4-11
Thank you again star. I was reading a paper where the author mentioned "if all the data errors are normally distributed" so now I understand it completely (correct me if I'm still wrong) first, I need to run regression then estimate residual and then have to use adtest on residual to see if errors are normally distributed or not if they are a linear fit is good approximation. I was really confused that how could we know the error in only observations. Thanks again
Star Strider
Star Strider 2016-4-11
My pleasure.
You are correct. The fit does not have to be linear (you can do a nonlinear fit to your data if that is appropriate). That aside, you would be checking to see if the residuals — the difference between the regression at every value of your independent variable and your dependent variable at those points — are normally distributed.

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Walter Roberson
Walter Roberson 2016-4-11
kstest() each of them individually.
If you want to know whether they come from the same normal distribution, see kstest2()
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amberly hadden
amberly hadden 2016-4-11
thank you Walter... In my understanding, real observations can rarely be from a normal distribution.

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