statistical test of normal and non-normal distributed data












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I have 2 samples of data. The first sample is the precision of the first algorithm A for 25 test cases and the second sample is precision for 25 test cases of second algorithm named B. I test both samples and first is normal distributed but second is non-normal distributed. (I check it with QQ plot, lillietest and shapiro-wilk test in R language).



Can I test this two samples with different distribution for example do they have an equal mean? If yes, which test should I use in this case?










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  • $begingroup$
    With samples as large as 25, it might be OK to use a two-sample t test, provided the second sample isn't very far from normal. It's difficult to say without seeing the data. // There are 'nonparametric' tests that do not assume normal data, but they do involve other assumptions. Without seeing the data it would not be responsible to recommend a nonparametric test--It might actually be worse than just doing a t test.
    $endgroup$
    – BruceET
    Dec 29 '18 at 22:10


















1












$begingroup$


I have 2 samples of data. The first sample is the precision of the first algorithm A for 25 test cases and the second sample is precision for 25 test cases of second algorithm named B. I test both samples and first is normal distributed but second is non-normal distributed. (I check it with QQ plot, lillietest and shapiro-wilk test in R language).



Can I test this two samples with different distribution for example do they have an equal mean? If yes, which test should I use in this case?










share|cite|improve this question









$endgroup$












  • $begingroup$
    With samples as large as 25, it might be OK to use a two-sample t test, provided the second sample isn't very far from normal. It's difficult to say without seeing the data. // There are 'nonparametric' tests that do not assume normal data, but they do involve other assumptions. Without seeing the data it would not be responsible to recommend a nonparametric test--It might actually be worse than just doing a t test.
    $endgroup$
    – BruceET
    Dec 29 '18 at 22:10
















1












1








1





$begingroup$


I have 2 samples of data. The first sample is the precision of the first algorithm A for 25 test cases and the second sample is precision for 25 test cases of second algorithm named B. I test both samples and first is normal distributed but second is non-normal distributed. (I check it with QQ plot, lillietest and shapiro-wilk test in R language).



Can I test this two samples with different distribution for example do they have an equal mean? If yes, which test should I use in this case?










share|cite|improve this question









$endgroup$




I have 2 samples of data. The first sample is the precision of the first algorithm A for 25 test cases and the second sample is precision for 25 test cases of second algorithm named B. I test both samples and first is normal distributed but second is non-normal distributed. (I check it with QQ plot, lillietest and shapiro-wilk test in R language).



Can I test this two samples with different distribution for example do they have an equal mean? If yes, which test should I use in this case?







statistics statistical-inference hypothesis-testing






share|cite|improve this question













share|cite|improve this question











share|cite|improve this question




share|cite|improve this question










asked Dec 29 '18 at 19:14









Jason WhiterJason Whiter

61




61












  • $begingroup$
    With samples as large as 25, it might be OK to use a two-sample t test, provided the second sample isn't very far from normal. It's difficult to say without seeing the data. // There are 'nonparametric' tests that do not assume normal data, but they do involve other assumptions. Without seeing the data it would not be responsible to recommend a nonparametric test--It might actually be worse than just doing a t test.
    $endgroup$
    – BruceET
    Dec 29 '18 at 22:10




















  • $begingroup$
    With samples as large as 25, it might be OK to use a two-sample t test, provided the second sample isn't very far from normal. It's difficult to say without seeing the data. // There are 'nonparametric' tests that do not assume normal data, but they do involve other assumptions. Without seeing the data it would not be responsible to recommend a nonparametric test--It might actually be worse than just doing a t test.
    $endgroup$
    – BruceET
    Dec 29 '18 at 22:10


















$begingroup$
With samples as large as 25, it might be OK to use a two-sample t test, provided the second sample isn't very far from normal. It's difficult to say without seeing the data. // There are 'nonparametric' tests that do not assume normal data, but they do involve other assumptions. Without seeing the data it would not be responsible to recommend a nonparametric test--It might actually be worse than just doing a t test.
$endgroup$
– BruceET
Dec 29 '18 at 22:10






$begingroup$
With samples as large as 25, it might be OK to use a two-sample t test, provided the second sample isn't very far from normal. It's difficult to say without seeing the data. // There are 'nonparametric' tests that do not assume normal data, but they do involve other assumptions. Without seeing the data it would not be responsible to recommend a nonparametric test--It might actually be worse than just doing a t test.
$endgroup$
– BruceET
Dec 29 '18 at 22:10












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