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| bio | website | |
|---|---|---|
| location | ||
| age | ||
| visits | member for | 2 years, 10 months |
| seen | Dec 9 '12 at 5:15 | |
| stats | profile views | 889 |
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Oct 19 |
awarded | Suffrage |
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Oct 19 |
comment |
Pearson's or Spearman's correlation with non-normal data @Srikant: I'm not sure it's a "secondary issue". You can compute anything after all -- it's the inference that matters. @Rob: your "if" qualifier is key here -- it seems to me that's central to this question. We can justify a whole lot with asymptotic hand waving; exceptions matter. |
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Oct 19 |
revised |
Pearson's or Spearman's correlation with non-normal data added 365 characters in body |
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Oct 19 |
revised |
Pearson's or Spearman's correlation with non-normal data added 33 characters in body |
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Oct 19 |
comment |
Pearson's or Spearman's correlation with non-normal data @Rob, @Srikant: True, I was thinking of significance testing. |
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Oct 19 |
revised |
Pearson's or Spearman's correlation with non-normal data added 178 characters in body |
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Oct 19 |
answered | Pearson's or Spearman's correlation with non-normal data |
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Oct 18 |
awarded | Mortarboard |
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Oct 18 |
answered | Bayes' Theorem and Agresti-Coull: Will it blend? |
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Oct 18 |
awarded | Nice Answer |
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Oct 18 |
answered | Show average instead of median in boxplot |
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Oct 18 |
comment |
What is the meaning of $\|a\|_p=\left(\sum _{i=1}^n \left|a_i(t)\right|{}^p\right){}^{\frac{1}{p}}$? I know, I liked it -- it's the right recommendation to make in case the OP wants to dig deeper. |
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Oct 18 |
comment |
What is the meaning of $\|a\|_p=\left(\sum _{i=1}^n \left|a_i(t)\right|{}^p\right){}^{\frac{1}{p}}$? +1. Though I'm not sure an analysis book, even if it is Rudin, is "approachable". ;-) |
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Oct 17 |
comment |
What is the meaning of $\|a\|_p=\left(\sum _{i=1}^n \left|a_i(t)\right|{}^p\right){}^{\frac{1}{p}}$? @Kaelin: Unfortunately I can't think of a text which discusses this in particular. I can tell you that the L1 distance is preferred since it's less sensitive to outliers. It's also related to distances between empirical distributions in probability theory ( L1 is twice the "total variation distance": en.wikipedia.org/wiki/Total_variation_distance ). |
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Oct 17 |
revised |
What is the meaning of $\|a\|_p=\left(\sum _{i=1}^n \left|a_i(t)\right|{}^p\right){}^{\frac{1}{p}}$? added 17 characters in body |
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Oct 17 |
answered | What is the meaning of $\|a\|_p=\left(\sum _{i=1}^n \left|a_i(t)\right|{}^p\right){}^{\frac{1}{p}}$? |
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Oct 17 |
answered | “Multiple response” analysis of arrest records |
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Oct 16 |
comment |
Calculating False Acceptance Rate for a Gaussian Distribution of scores thank you! |
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Oct 16 |
comment |
Calculating False Acceptance Rate for a Gaussian Distribution of scores That's impressive; please share. :) |
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Oct 15 |
revised |
How to parameterize the ratio of two normally distributed variables, or the inverse of one? added 338 characters in body; added 2 characters in body |
