Hi, let ## r_1,..,r_n## be residuals in a given regression. I am trying to understand how the test for normality(adsbygoogle = window.adsbygoogle || []).push({});

works. This is how I think it works:

We take the sampling mean , i.e., ##r:=\frac {1}{n} \Sigma r_i / n## , and the sampling standard deviation ##\sigma_{r_i} ##. Then, if the residuals are normally-distributed, we could find the z-values for each of the ## r_i## , using ## r, \sigma_{r_i} / \sqrt n ## , and we compare these to the actual z-values of the actual data. And, overall (this is an observation, not part of the test), around 68.6% of data values should be within 1-##\sigma_{r_i}## of the sample mean ##r## (i.e., the sample data should follow the 68-95-99.7 rule). Is that it?

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# Test for Normality of Residuals -- Is this how it Works?

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