statistics: add covariance, Pearson's correlation, and simple linear regression #82671

twolodzko · 2019-10-15T21:40:09Z

BPO	38490
Nosy	@tim-one, @rhettinger, @taleinat, @stevendaprano, @csabella, @twolodzko
PRs	bpo-38490: statistics: Add covariance, Pearson's correlation, and simple linear regression #16813

^{Note: these values reflect the state of the issue at the time it was migrated and might not reflect the current state.}

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GitHub fields:

assignee = 'https://github.com/stevendaprano'
closed_at = <Date 2021-04-25.11:47:06.058>
created_at = <Date 2019-10-15.21:40:09.493>
labels = ['type-feature', 'library', '3.9']
title = "statistics: add covariance, Pearson's correlation, and simple linear regression"
updated_at = <Date 2021-04-25.11:47:06.057>
user = 'https://github.com/twolodzko'

bugs.python.org fields:

activity = <Date 2021-04-25.11:47:06.057>
actor = 'taleinat'
assignee = 'steven.daprano'
closed = True
closed_date = <Date 2021-04-25.11:47:06.058>
closer = 'taleinat'
components = ['Library (Lib)']
creation = <Date 2019-10-15.21:40:09.493>
creator = 'twolodzko'
dependencies = []
files = []
hgrepos = []
issue_num = 38490
keywords = ['patch']
message_count = 12.0
messages = ['354754', '354763', '354775', '354786', '354790', '354842', '354863', '369647', '373529', '378061', '391856', '391857']
nosy_count = 6.0
nosy_names = ['tim.peters', 'rhettinger', 'taleinat', 'steven.daprano', 'cheryl.sabella', 'twolodzko']
pr_nums = ['16813']
priority = 'normal'
resolution = 'fixed'
stage = 'resolved'
status = 'closed'
superseder = None
type = 'enhancement'
url = 'https://bugs.python.org/issue38490'
versions = ['Python 3.9']

twolodzko · 2019-10-15T21:40:09Z

Covariance and Pearson's correlation are one of the most basic bivariate statistics.

https://en.wikipedia.org/wiki/Covariance
https://en.wikipedia.org/wiki/Pearson_correlation_coefficient

rhettinger · 2019-10-16T00:50:55Z

These two functions are right on the boundary edge of what the statistics module is trying to do, """The module is not intended to be a competitor to third-party libraries such as NumPy, SciPy, or proprietary full-featured statistics packages aimed at professional statisticians such as Minitab, SAS and Matlab. It is aimed at the level of graphing and scientific calculators."""

It is debatable which side of the boundary they belong to. MS Excel has both of these functions, but it isn't a given that a scientific calculator would have them.

Also, the current functions require only high-school level knowledge, but these two require more skill to learn, use, and interpret.

twolodzko · 2019-10-16T06:56:02Z

I think I see your point, that the module is intended for the most basic
features, but I would argue that correlation is one of such "most basic"
statistics.

Correlation and covariance can be thought as equivalents for standard
deviation and variance, but when we are talking about pairs of variables.
Moreover it is probably used much more often then things like geometric or
harmonic mean, that are implemented in the package. Covariance is probably
more esoteric for most non-statisticians, but in my PR (
#16813 ) I implemented it for
completeness and as a helper function for the correlation coefficient.

TL;DR those are basic statistics. They would make the module much more
helpful, since the basic statistics could be calculated using base python
w/o external libraries. They are also trivial to implemented (done this in
PR) and do not need much more maintenance then the other functionalities in
the module.

Tim

śr., 16 paź 2019 o 02:50 Raymond Hettinger <report@bugs.python.org>
napisał(a):

Raymond Hettinger <raymond.hettinger@gmail.com> added the comment:

These two functions are right on the boundary edge of what the statistics
module is trying to do, """The module is not intended to be a competitor to
third-party libraries such as NumPy, SciPy, or proprietary full-featured
statistics packages aimed at professional statisticians such as Minitab,
SAS and Matlab. It is aimed at the level of graphing and scientific
calculators."""

It is debatable which side of the boundary they belong to. MS Excel has
both of these functions, but it isn't a given that a scientific calculator
would have them.

Also, the current functions require only high-school level knowledge, but
these two require more skill to learn, use, and interpret.

----------
assignee: -> steven.daprano
nosy: +rhettinger, steven.daprano

Python tracker <report@bugs.python.org>
<https://bugs.python.org/issue38490\>

stevendaprano · 2019-10-16T08:47:10Z

I can't speak for other countries, but in Australia, secondary school
mathematics teaches correlation coefficient and linear regression from
Year 11 onwards (typically ages 16 or 17). Covariance is not itself
taught, and as far as I can tell neither the TI-83 nor NSpire
provides a built-in covariance command.

On the other hand, other calculators such as the HP-48GX do.

Oddly, Excel provides the population (not sample) covariance:

https://support.office.com/en-us/article/COVARIANCE-P-function-6F0E1E6D-956D-4E4B-9943-CFEF0BF9EDFC

OpenOffice and LibreOffice also provide a covariance function.

I think that supporting correlation coefficient r and linear
regression would be clear wins, from the perspective of secondary school
maths. But as far as covariance goes, it would help convince me if you
had either:

evidence that covariance is taught in secondary schools, or at
least first year undergraduate statistics;
that it has use-cases beyond "helper for calculating r";
or that there is demand for it from people who want covariance
but can't, or don't want to, use numpy/scipy.

twolodzko · 2019-10-16T09:25:16Z

In case there is agreement with Steven, I will add simple linear regression
( https://en.wikipedia.org/wiki/Simple_linear_regression ) in the same PR,
since it is just:

slope = correlation(x, y) * ( stdev(y) / stdev(x) )
intercept = mean(y) - slope * mean(x)

As about covariance, I see your points, but why not keeping it "because we
can"? It can be useful for some users and the functionality still needs to
be implemented to have correlation coefficient.

On Wed, Oct 16, 2019 at 10:47 AM Steven D'Aprano <report@bugs.python.org>
wrote:

Steven D'Aprano steve+python@pearwood.info added the comment:

I can't speak for other countries, but in Australia, secondary school
mathematics teaches correlation coefficient and linear regression from
Year 11 onwards (typically ages 16 or 17). Covariance is not itself
taught, and as far as I can tell neither the TI-83 nor NSpire
provides a built-in covariance command.

On the other hand, other calculators such as the HP-48GX do.

Oddly, Excel provides the population (not sample) covariance:

https://support.office.com/en-us/article/COVARIANCE-P-function-6F0E1E6D-956D-4E4B-9943-CFEF0BF9EDFC

OpenOffice and LibreOffice also provide a covariance function.

I think that supporting correlation coefficient r and linear
regression would be clear wins, from the perspective of secondary school
maths. But as far as covariance goes, it would help convince me if you
had either:

evidence that covariance is taught in secondary schools, or at
least first year undergraduate statistics;

that it has use-cases beyond "helper for calculating r";

or that there is demand for it from people who want covariance
but can't, or don't want to, use numpy/scipy.

----------

Python tracker <report@bugs.python.org>
<https://bugs.python.org/issue38490\>

twolodzko · 2019-10-17T14:13:22Z

I expanded my PR to add simple linear regression. I also created
documentation for the new functionalities.

As about covariance, we can simply not expose it to the users, but I'm not
convinced that there is any gain in keeping it hidden from the users.

Tim

On Wed, Oct 16, 2019 at 11:25 AM Tymek Wołodźko <report@bugs.python.org>
wrote:

Tymek Wołodźko twolodzko@gmail.com added the comment:

In case there is agreement with Steven, I will add simple linear regression
( https://en.wikipedia.org/wiki/Simple_linear_regression ) in the same PR,
since it is just:

slope = correlation(x, y) * ( stdev(y) / stdev(x) )
intercept = mean(y) - slope * mean(x)

As about covariance, I see your points, but why not keeping it "because we
can"? It can be useful for some users and the functionality still needs to
be implemented to have correlation coefficient.

On Wed, Oct 16, 2019 at 10:47 AM Steven D'Aprano report@bugs.python.org
wrote:

Steven D'Aprano steve+python@pearwood.info added the comment:

I can't speak for other countries, but in Australia, secondary school
mathematics teaches correlation coefficient and linear regression from
Year 11 onwards (typically ages 16 or 17). Covariance is not itself
taught, and as far as I can tell neither the TI-83 nor NSpire
provides a built-in covariance command.

On the other hand, other calculators such as the HP-48GX do.

Oddly, Excel provides the population (not sample) covariance:

https://support.office.com/en-us/article/COVARIANCE-P-function-6F0E1E6D-956D-4E4B-9943-CFEF0BF9EDFC

OpenOffice and LibreOffice also provide a covariance function.

I think that supporting correlation coefficient r and linear
regression would be clear wins, from the perspective of secondary school
maths. But as far as covariance goes, it would help convince me if you
had either:

evidence that covariance is taught in secondary schools, or at
least first year undergraduate statistics;

that it has use-cases beyond "helper for calculating r";

or that there is demand for it from people who want covariance
but can't, or don't want to, use numpy/scipy.

----------
>
> _______________________________________
> Python tracker <report@bugs.python.org>
> <https://bugs.python.org/issue38490\>
> _______________________________________
>

----------

Python tracker <report@bugs.python.org>
<https://bugs.python.org/issue38490\>

tim-one · 2019-10-18T05:05:03Z

I'm in favor of adding all of this (covariance, coefficient, linear regression). It's still at the level of elementary statistics, and even taught in watered down "business statistics" classes. It's about the minimum that can be done beyond single-variable stats.

But I also think this defines the limit of what the core "should" include in this area.

csabella · 2020-05-22T20:45:26Z

@steven.daprano and @tim.peters, please take a look at the PR as it is just waiting on your approval. Thanks!

twolodzko · 2020-07-11T17:26:07Z

Is there anything more I should do about the PR?

Sincerely,
Tim

On Fri, May 22, 2020 at 10:45 PM Cheryl Sabella <report@bugs.python.org>
wrote:

Cheryl Sabella <cheryl.sabella@gmail.com> added the comment:

@steven.daprano and @tim.peters, please take a look at the PR as it is
just waiting on your approval. Thanks!

----------
nosy: +cheryl.sabella

Python tracker <report@bugs.python.org>
<https://bugs.python.org/issue38490\>

taleinat · 2020-10-05T16:35:50Z

Given the discussion here and the state of the attached PR, I intend to merge the PR in several weeks, unless someone has anything else to say.

taleinat · 2021-04-25T11:45:23Z

New changeset 09aa6f9 by Tymoteusz Wołodźko in branch 'master':
bpo-38490: statistics: Add covariance, Pearson's correlation, and simple linear regression (bpo-16813)
09aa6f9

taleinat · 2021-04-25T11:47:06Z

Thanks for the suggestion, PR, and great heaps of patience and perseverance, Tymek!

twolodzko mannequin added 3.8 only security fixes 3.9 only security fixes type-feature A feature request or enhancement labels Oct 15, 2019

rhettinger assigned stevendaprano Oct 16, 2019

rhettinger added stdlib Python modules in the Lib dir and removed 3.8 only security fixes labels Oct 16, 2019

twolodzko mannequin changed the title ~~statistics: add covariance and Pearson's correlation~~ statistics: add covariance, Pearson's correlation, and simple linear regression Oct 22, 2019

taleinat closed this as completed Apr 25, 2021

ezio-melotti transferred this issue from another repository Apr 10, 2022

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statistics: add covariance, Pearson's correlation, and simple linear regression #82671

statistics: add covariance, Pearson's correlation, and simple linear regression #82671

twolodzko mannequin commented Oct 15, 2019

twolodzko mannequin commented Oct 15, 2019

rhettinger commented Oct 16, 2019

twolodzko mannequin commented Oct 16, 2019

stevendaprano commented Oct 16, 2019

twolodzko mannequin commented Oct 16, 2019

twolodzko mannequin commented Oct 17, 2019

tim-one commented Oct 18, 2019

csabella commented May 22, 2020

twolodzko mannequin commented Jul 11, 2020

taleinat commented Oct 5, 2020

taleinat commented Apr 25, 2021

taleinat commented Apr 25, 2021

statistics: add covariance, Pearson's correlation, and simple linear regression #82671

statistics: add covariance, Pearson's correlation, and simple linear regression #82671

Comments

twolodzko mannequin commented Oct 15, 2019

twolodzko mannequin commented Oct 15, 2019

rhettinger commented Oct 16, 2019

twolodzko mannequin commented Oct 16, 2019

stevendaprano commented Oct 16, 2019

twolodzko mannequin commented Oct 16, 2019

twolodzko mannequin commented Oct 17, 2019

tim-one commented Oct 18, 2019

csabella commented May 22, 2020

twolodzko mannequin commented Jul 11, 2020

taleinat commented Oct 5, 2020

taleinat commented Apr 25, 2021

taleinat commented Apr 25, 2021