Re: Textbook Recommendations

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Thank you Josef!
It's on the reading list.

On Wed, Feb 22, 2023 at 4:02 PM <[email protected]> wrote:

> I just saw a recent book using Python
>
> Wiley.com. =E2=80=9CApplied Univariate, Bivariate, and Multivariate Stati=
stics
> Using Python: A Beginner=E2=80=99s Guide to Advanced Data Analysis | Wile=
y.=E2=80=9D
> Accessed February 22, 2023.
> https://www.wiley.com/en-us/Applied+Univariate%2C+Bivariate%2C+and+Multiv=
ariate+Statistics+Using+Python%3A+A+Beginner%27s+Guide+to+Advanced+Data+Ana=
lysis-p-9781119578185
> .
>
>
> On Wed, Feb 15, 2023 at 5:56 PM Britta Smith <[email protected]>
> wrote:
>
>> thank you sean
>>
>> On Wed, Feb 15, 2023 at 11:38 AM Sean Berry <[email protected]> wrote:
>>
>>> Hi Britta,
>>>
>>> Here is one that includes regression and machine learning that I've
>>> found useful:
>>>
>>> Hands-On machine learning with scikit-learn, keras, & tensor flow.
>>> Written by Aurelien Geron.
>>>
>>> Sean
>>>
>>> On Wed, Feb 15, 2023, 9:46 AM Albert Steppi <[email protected]>
>>> wrote:
>>>
>>>> Hi Britta,
>>>>
>>>> I haven't read anything Python specific, but I like the following book=
s:
>>>>
>>>> For basic introductory stats, Freedman, Pisani, and Purves
>>>> <https://wwnorton.com/books/Statistics/>
>>>>
>>>> As a follow up, Freedman's Statistical Models: Theory and Practice
>>>> <https://www.cambridge.org/core/books/statistical-models/68F8872C7788A=
F62BD6513F7071EE1BA#fndtn-information>,
>>>> teaches one to think critically about regression modeling and its
>>>> limitations.
>>>>
>>>> Efron and Hasties Computer Age Statistical Inference
>>>> <https://hastie.su.domains/CASI_files/PDF/casi.pdf>, for a very broad
>>>> overview of a wide range of computational statistics topics.
>>>>
>>>> Hastie, Tibshirani, and Friedman's Elements of Statistical Learning
>>>> <https://hastie.su.domains/Papers/ESLII.pdf>, classic introduction to
>>>> statistical machine learning.
>>>>
>>>> Gelman et al's Bayesian Data Analysis
>>>> <http://www.stat.columbia.edu/~gelman/book/BDA3.pdf> for Bayesian
>>>> modeling, but I haven't read any other books on this topic.
>>>>
>>>> I tend to just read the relevant documentation (pymc, pyro, pytorch,
>>>> scikit-learn, scipy, statsmodels) to figure out how to do things in Py=
thon.
>>>> Hopefully someone else can chime in with more Python specific books.
>>>>
>>>> Best,
>>>> Albert
>>>>
>>>>
>>>>
>>>> On Wed, Feb 15, 2023 at 10:31 AM Britta Smith <[email protected]>
>>>> wrote:
>>>>
>>>>> Dear SciPy community,
>>>>> What are your recommendations for textbooks concerning statistics and
>>>>> data science? That hopefully go into depth about regression, and hope=
fully
>>>>> python.
>>>>> Many thanks,
>>>>> Britta
>>>>> _______________________________________________
>>>>> SciPy-User mailing list -- [email protected]
>>>>> To unsubscribe send an email to [email protected]
>>>>> https://mail.python.org/mailman3/lists/scipy-user.python.org/
>>>>> Member address: [email protected]
>>>>>
>>>> _______________________________________________
>>>> SciPy-User mailing list -- [email protected]
>>>> To unsubscribe send an email to [email protected]
>>>> https://mail.python.org/mailman3/lists/scipy-user.python.org/
>>>> Member address: [email protected]
>>>>
>>> _______________________________________________
>>> SciPy-User mailing list -- [email protected]
>>> To unsubscribe send an email to [email protected]
>>> https://mail.python.org/mailman3/lists/scipy-user.python.org/
>>> Member address: [email protected]
>>>
>> _______________________________________________
>> SciPy-User mailing list -- [email protected]
>> To unsubscribe send an email to [email protected]
>> https://mail.python.org/mailman3/lists/scipy-user.python.org/
>> Member address: [email protected]
>>
> _______________________________________________
> SciPy-User mailing list -- [email protected]
> To unsubscribe send an email to [email protected]
> https://mail.python.org/mailman3/lists/scipy-user.python.org/
> Member address: [email protected]
>

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<div dir=3D"ltr"><div class=3D"gmail_default" style=3D"font-family:tahoma,s=
ans-serif;font-size:small;color:#3d85c6">Thank you Josef!</div><div class=
=3D"gmail_default" style=3D"font-family:tahoma,sans-serif;font-size:small;c=
olor:#3d85c6">It&#39;s on the reading list.</div></div><br><div class=3D"gm=
ail_quote"><div dir=3D"ltr" class=3D"gmail_attr">On Wed, Feb 22, 2023 at 4:=
02 PM &lt;<a href=3D"mailto:[email protected]">[email protected]</a>&=
gt; wrote:<br></div><blockquote class=3D"gmail_quote" style=3D"margin:0px 0=
px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div =
dir=3D"ltr">I just saw a recent book using Python<div><br></div><div><div s=
tyle=3D"line-height:1.35;margin-left:2em">
  <div>Wiley.com. =E2=80=9CApplied Univariate, Bivariate, and Multivariate =
Statistics Using Python: A Beginner=E2=80=99s Guide to Advanced Data Analys=
is | Wiley.=E2=80=9D Accessed February 22, 2023. <a href=3D"https://www.wil=
ey.com/en-us/Applied+Univariate%2C+Bivariate%2C+and+Multivariate+Statistics=
+Using+Python%3A+A+Beginner%27s+Guide+to+Advanced+Data+Analysis-p-978111957=
8185" target=3D"_blank">https://www.wiley.com/en-us/Applied+Univariate%2C+B=
ivariate%2C+and+Multivariate+Statistics+Using+Python%3A+A+Beginner%27s+Guid=
e+to+Advanced+Data+Analysis-p-9781119578185</a>.</div><div><br></div>
  <span title=3D"url_ver=3DZ39.88-2004&amp;ctx_ver=3DZ39.88-2004&amp;rfr_id=
=3Dinfo%3Asid%2Fzotero.org%3A2&amp;rft_val_fmt=3Dinfo%3Aofi%2Ffmt%3Akev%3Am=
tx%3Adc&amp;rft.type=3Dwebpage&amp;rft.title=3DApplied%20Univariate%2C%20Bi=
variate%2C%20and%20Multivariate%20Statistics%20Using%20Python%3A%20A%20Begi=
nner&#39;s%20Guide%20to%20Advanced%20Data%20Analysis%20%7C%20Wiley&amp;rft.=
description=3DApplied%20Univariate%2C%20Bivariate%2C%20and%20Multivariate%2=
0Statistics%20Using%20Python%20A%20practical%2C%20%E2%80%9Chow-to%E2%80%9D%=
20reference%20for%20anyone%20performing%20essential%20statistical%20analyse=
s%20and%20data%20management%20tasks%20in%20PythonApplied%20Univariate%2C%20=
Bivariate%2C%20and%20Multivariate%20Statistics%20Using%20Python%20delivers%=
20a%20comprehensive%20introduction%20to%20a%20wide%20range%20of%20statistic=
al%20methods%20performed%20using%20Python%20in%20a%20single%2C%20one-stop%2=
0reference.%20The%20book%20contains%20user-friendly%20guidance%20and%20inst=
ructions%20on%20using%20Python%20to%20run%20a%20variety%20of%20statistical%=
20procedures%20without%20getting%20bogged%20down%20in%20unnecessary%20theor=
y.%20Throughout%2C%20the%20author%20emphasizes%20a%20set%20of%20computation=
al%20tools%20used%20in%20the%20discovery%20of%20empirical%20patterns%2C%20a=
s%20well%20as%20several%20popular%20statistical%20analyses%20and%20data%20m=
anagement%20tasks%20that%20can%20be%20immediately%20applied.Most%20of%20the=
%20datasets%20used%20in%20the%20book%20are%20small%20enough%20to%20be%20eas=
ily%20entered%20into%20Python%20manually%2C%20though%20they%20can%20also%20=
be%20downloaded%20for%20free%20from%20www.datapsyc.com.%20Only%20minimal%20=
knowledge%20of%20statistics%20is%20assumed%2C%20making%20the%20book%20perfe=
ct%20for%20those%20seeking%20an%20easily%20accessible%20toolkit%20for%20sta=
tistical%20analysis%20with%20Python.%20Applied%20Univariate%2C%20Bivariate%=
2C%20and%20Multivariate%20Statistics%20Using%20Python%20represents%20the%20=
fastest%20way%20to%20learn%20how%20to%20analyze%20data%20with%20Python.Read=
ers%20will%20also%20benefit%20from%20the%20inclusion%20of%3AA%20review%20of=
%20essential%20statistical%20principles%2C%20including%20types%20of%20data%=
2C%20measurement%2C%20significance%20tests%2C%20significance%20levels%2C%20=
and%20type%20I%20and%20type%20II%20errorsAn%20introduction%20to%20Python%2C=
%20exploring%20how%20to%20communicate%20with%20PythonA%20treatment%20of%20e=
xploratory%20data%20analysis%2C%20basic%20statistics%20and%20visual%20displ=
ays%2C%20including%20frequencies%20and%20descriptives%2C%20q-q%20plots%2C%2=
0box-and-whisker%20plots%2C%20and%20data%20managementAn%20introduction%20to=
%20topics%20such%20as%20ANOVA%2C%20MANOVA%20and%20discriminant%20analysis%2=
C%20regression%2C%20principal%20components%20analysis%2C%20factor%20analysi=
s%2C%20cluster%20analysis%2C%20among%20others%2C%20exploring%20the%20nature=
%20of%20what%20these%20techniques%20can%20vs.%20cannot%20do%20on%20a%20meth=
odological%20levelPerfect%20for%20undergraduate%20and%20graduate%20students=
%20in%20the%20social%2C%20behavioral%2C%20and%20natural%20sciences%2C%20App=
lied%20Univariate%2C%20Bivariate%2C%20and%20Multivariate%20Statistics%20Usi=
ng%20Python%20will%20also%20earn%20a%20place%20in%20the%20libraries%20of%20=
researchers%20and%20data%20analysts%20seeking%20a%20quick%20go-to%20resourc=
e%20for%20univariate%2C%20bivariate%2C%20and%20multivariate%20analysis%20in=
%20Python.&amp;rft.identifier=3Dhttps%3A%2F%2Fwww.wiley.com%2Fen-us%2FAppli=
ed%2BUnivariate%252C%2BBivariate%252C%2Band%2BMultivariate%2BStatistics%2BU=
sing%2BPython%253A%2BA%2BBeginner%2527s%2BGuide%2Bto%2BAdvanced%2BData%2BAn=
alysis-p-9781119578185&amp;rft.language=3Den-us"></span>
</div></div></div><br><div class=3D"gmail_quote"><div dir=3D"ltr" class=3D"=
gmail_attr">On Wed, Feb 15, 2023 at 5:56 PM Britta Smith &lt;<a href=3D"mai=
lto:[email protected]" target=3D"_blank">[email protected]</a>&gt; =
wrote:<br></div><blockquote class=3D"gmail_quote" style=3D"margin:0px 0px 0=
px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir=
=3D"ltr"><div class=3D"gmail_default" style=3D"font-family:tahoma,sans-seri=
f;font-size:small;color:rgb(61,133,198)">thank you sean</div></div><br><div=
 class=3D"gmail_quote"><div dir=3D"ltr" class=3D"gmail_attr">On Wed, Feb 15=
, 2023 at 11:38 AM Sean Berry &lt;<a href=3D"mailto:[email protected]" tar=
get=3D"_blank">[email protected]</a>&gt; wrote:<br></div><blockquote class=
=3D"gmail_quote" style=3D"margin:0px 0px 0px 0.8ex;border-left:1px solid rg=
b(204,204,204);padding-left:1ex"><div dir=3D"auto">Hi Britta,=C2=A0<div dir=
=3D"auto"><br></div><div dir=3D"auto">Here is one that includes regression =
and machine learning that I&#39;ve found useful:</div><div dir=3D"auto"><br=
></div><div dir=3D"auto">Hands-On machine learning with scikit-learn, keras=
, &amp; tensor flow. Written by Aurelien Geron.</div><div dir=3D"auto"><br>=
</div><div dir=3D"auto">Sean</div></div><br><div class=3D"gmail_quote"><div=
 dir=3D"ltr" class=3D"gmail_attr">On Wed, Feb 15, 2023, 9:46 AM Albert Step=
pi &lt;<a href=3D"mailto:[email protected]" target=3D"_blank">albert.=
[email protected]</a>&gt; wrote:<br></div><blockquote class=3D"gmail_quote" =
style=3D"margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);pa=
dding-left:1ex"><div dir=3D"ltr"><div>Hi Britta,<br></div><div><br></div><d=
iv>I haven&#39;t read anything Python specific, but I like the following bo=
oks:</div><div><br></div><div>For basic introductory stats, <a href=3D"http=
s://wwnorton.com/books/Statistics/" rel=3D"noreferrer" target=3D"_blank">Fr=
eedman, Pisani, and Purves</a></div><div><br></div><div>As a follow up, Fre=
edman&#39;s <a href=3D"https://www.cambridge.org/core/books/statistical-mod=
els/68F8872C7788AF62BD6513F7071EE1BA#fndtn-information" rel=3D"noreferrer" =
target=3D"_blank">Statistical Models: Theory and Practice</a>, teaches one =
to think critically about regression modeling and its limitations.</div><di=
v><br></div><div>Efron and Hasties <a href=3D"https://hastie.su.domains/CAS=
I_files/PDF/casi.pdf" rel=3D"noreferrer" target=3D"_blank">Computer Age Sta=
tistical Inference</a>, for a very broad overview of a wide range of comput=
ational statistics topics.</div><div><br></div><div>Hastie, Tibshirani, and=
 Friedman&#39;s <a href=3D"https://hastie.su.domains/Papers/ESLII.pdf" rel=
=3D"noreferrer" target=3D"_blank">Elements of Statistical Learning</a>, cla=
ssic introduction to statistical machine learning.</div><div><br></div><div=
>Gelman et al&#39;s <a href=3D"http://www.stat.columbia.edu/~gelman/book/BD=
A3.pdf" rel=3D"noreferrer" target=3D"_blank">Bayesian Data Analysis</a> for=
 Bayesian modeling, but I haven&#39;t read any other books on this topic.</=
div><div><br></div><div>I tend to just read the relevant documentation (pym=
c, pyro, pytorch, scikit-learn, scipy, statsmodels) to figure out how to do=
 things in Python. Hopefully someone else can chime in with more Python spe=
cific books.</div><div><br></div><div>Best,</div><div>Albert<br></div><div>=
<br></div><div><br></div></div><br><div class=3D"gmail_quote"><div dir=3D"l=
tr" class=3D"gmail_attr">On Wed, Feb 15, 2023 at 10:31 AM Britta Smith &lt;=
<a href=3D"mailto:[email protected]" rel=3D"noreferrer" target=3D"_blan=
k">[email protected]</a>&gt; wrote:<br></div><blockquote class=3D"gmail=
_quote" style=3D"margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204=
,204);padding-left:1ex">Dear SciPy community,<div dir=3D"auto">What are you=
r recommendations for textbooks concerning statistics and data science? Tha=
t hopefully go into depth about regression, and hopefully python.</div><div=
 dir=3D"auto">Many thanks,</div><div dir=3D"auto">Britta</div>
_______________________________________________<br>
SciPy-User mailing list -- <a href=3D"mailto:[email protected]" rel=3D"=
noreferrer" target=3D"_blank">[email protected]</a><br>
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rg" rel=3D"noreferrer" target=3D"_blank">[email protected]</a><br=
>
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r" target=3D"_blank">[email protected]</a><br>
</blockquote></div>
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