R help - Jul 2022 - the quantile function and problems.

? Thu, 14 Jul 2022 14:58:17 +0200
Uwe Brauer <oub at mat.ucm.es> ?????:
> What turns me crazy is that the way R, matlab and the JCR calculate
> the quartiles gives different results.
R by itself can give up to 9 slightly different results:

sapply(1:9, function(type) quantile(1:267, 1:3/4, type = type))
#     [,1] [,2] [,3]   [,4]   [,5] [,6]  [,7]      [,8]     [,9]
# 25%   67   67   67  66.75  67.25   67  67.5  67.16667  67.1875
# 50%  134  134  134 133.50 134.00  134 134.0 134.00000 134.0000
# 75%  201  201  200 200.25 200.75  201 200.5 200.83333 200.8125

Choose the ones that fit your ideas of quantile best. See ?quantile for
more info.

-- 
Best regards,
Ivan

Does the choice in how the quantile is calculated influence the validity of a
statistical test for differences in the median?
Regards,
Tim

-----Original Message-----
From: R-help <r-help-bounces at r-project.org> On Behalf Of Ivan Krylov
Sent: Friday, July 15, 2022 2:21 AM
To: Uwe Brauer <oub at mat.ucm.es>
Cc: r-help at r-project.org
Subject: Re: [R] the quantile function and problems.

[External Email]

? Thu, 14 Jul 2022 14:58:17 +0200
Uwe Brauer <oub at mat.ucm.es> ?????:
> What turns me crazy is that the way R, matlab and the JCR calculate 
> the quartiles gives different results.
R by itself can give up to 9 slightly different results:

sapply(1:9, function(type) quantile(1:267, 1:3/4, type = type))
#     [,1] [,2] [,3]   [,4]   [,5] [,6]  [,7]      [,8]     [,9]
# 25%   67   67   67  66.75  67.25   67  67.5  67.16667  67.1875
# 50%  134  134  134 133.50 134.00  134 134.0 134.00000 134.0000 # 75%  201  201
200 200.25 200.75  201 200.5 200.83333 200.8125

Choose the ones that fit your ideas of quantile best. See ?quantile for more
info.

--
Best regards,
Ivan

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>>> "IK" == Ivan Krylov <krylov.r00t at gmail.com>
writes:
> ? Thu, 14 Jul 2022 14:58:17 +0200
> Uwe Brauer <oub at mat.ucm.es> ?????:
>> What turns me crazy is that the way R, matlab and the JCR calculate
>> the quartiles gives different results.
> R by itself can give up to 9 slightly different results:
> sapply(1:9, function(type) quantile(1:267, 1:3/4, type = type))
> #     [,1] [,2] [,3]   [,4]   [,5] [,6]  [,7]      [,8]     [,9]
> # 25%   67   67   67  66.75  67.25   67  67.5  67.16667  67.1875
> # 50%  134  134  134 133.50 134.00  134 134.0 134.00000 134.0000
> # 75%  201  201  200 200.25 200.75  201 200.5 200.83333 200.8125
Thanks, number 3 is the best for my purpose. 

Very useful



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