# Statistical checks for regression, covariance, etc?

 0 Suppose I have some input vector(s) of scientific data. Assuming I at least know which ones are completely independent, and have some other(s) of which dependence is uncertain; what are some good sage functions to throw at the vector(s) to check for basic statistical parity/significance? I know this question is very broad, so it's a basic howto rhetorical question. A continuous or discrete first order relationship is a fine intro; though more complex scenarios tend to be interesting. asked Aug 29 '10 ccanonc 487 ● 5 ● 18 ● 34

 1 Hello, Depending on what you mean by "scientific data" the answer would be different. If they are in a finite set say {True, False} then you can make a chi^2 test. If they are infinite but can be ordinate then you can perform a Mann-Whitney (or Wilcoxon or Wilcoxon-Mann-Whitney) test... In the two preceding cases you should use R (which is included in Sage) which is a toolbox for statistics. More precisely you can look at sage: r.chisq_test? sage: r.wilcox_test?  (the r. means that you will use R) posted Aug 30 '10 vdelecroix 1422 ● 6 ● 22 ● 39

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