![]() In all cases, a chi-square test with k 32 bins was applied to test for normally distributed data. ![]() Starting with your last questions first: yes, the $\chi^2$ distribution with $k$ degrees of freedom is normally defiined as being the sum of the squares of $k$ independent $N(0,1)$ distributions. We know that when you have a sample and estimate the mean, you have n 1 degrees of freedom, where n is the sample size. Chi-Square Test Example: We generated 1,000 random numbers for normal, double exponential, t with 3 degrees of freedom, and lognormal distributions.
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