A primer on nonparametric analysis. / Volume I / / Shahdad Naghshpour.
Nonparametric statistics provide a scientific methodology for cases where customary statistics are not applicable. Nonparametric statistics are used when the requirements for parametric analysis fail, such as when data are not normally distributed or the sample size is too small. The method provides...
Saved in:
Superior document: | Economics collection, |
---|---|
VerfasserIn: | |
Place / Publishing House: | New York, New York (222 East 46th Street, New York, NY 10017) : : Business Expert Press,, 2016. |
Year of Publication: | 2016 |
Edition: | First edition. |
Language: | English |
Series: | Economics collection.
|
Online Access: | |
Physical Description: | 1 online resource (xxvii, 120 pages) |
Notes: | Includes index. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
5004648712 |
---|---|
ctrlnum |
(MiAaPQ)5004648712 (Au-PeEL)EBL4648712 (CaPaEBR)ebr11249676 (CaONFJC)MIL949214 (OCoLC)957588810 |
collection |
bib_alma |
record_format |
marc |
spelling |
Naghshpour, Shahdad., author. A primer on nonparametric analysis. Volume I / Shahdad Naghshpour. First edition. New York, New York (222 East 46th Street, New York, NY 10017) : Business Expert Press, 2016. 1 online resource (xxvii, 120 pages) text rdacontent computer rdamedia online resource rdacarrier Economics collection, 2163-7628 Includes index. Section I. One-sample tests -- 1. Goodness of fit tests -- 2. Randomness tests -- 3. One-sample location inference -- Section II. One-sample tests -- 4. Comparing two unrelated samples: the Mann-Whitney U test -- 5. Goodness of fit for two samples -- Index. Access restricted to authorized users and institutions. Nonparametric statistics provide a scientific methodology for cases where customary statistics are not applicable. Nonparametric statistics are used when the requirements for parametric analysis fail, such as when data are not normally distributed or the sample size is too small. The method provides an alternative for such cases and is often nearly as powerful as parametric statistics. Another advantage of nonparametric statistics is that it offers analytical methods that are not available otherwise. In social sciences, often, it is not possible to obtain measurements, which renders customary analysis impossible. For example, it is not possible to measure utility but is possible to rank preference, which is based on the unmeasurable utility. Nonparametric methods provide theoretically valid options for analysis, making the use of unscientific methods unnecessary. Nonparametric methods are intuitive and simple to comprehend, which helps researchers in the social sciences understand the methods in spite of lacking mathematical rigor needed in analytical methods customarily used in science. The only prerequisite for this book is high school level elementary algebra. This book is a methodology book and bypasses theoretical proofs while providing comprehensive explanations of the logic behind the methods and ample examples, which are all solved using direct computations as well as by using Stata. The book is arranged into two integrated volumes. Although each volume, and for that matter each chapter, can be used separately, it is advisable to read as much of both volumes as possible; because familiarity with what is applicable for different problems will enhance capabilities. It is recommended that everyone read the Introduction and Chapter 1 because determining whether data are random or normally distributed is essential in the selection of parametric versus nonparametric methods. Title from PDF title page (viewed on August 29, 2016). Electronic reproduction. Ann Arbor, MI : ProQuest, 2016. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries. Nonparametric statistics. Nonparametric statistics median order statistics rank one sample two samples several samples multiple comparison normality skewness Electronic books. Print version: 9781631574450 ProQuest (Firm) Economics collection. 2163-7628 https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=4648712 Click to View |
language |
English |
format |
eBook |
author |
Naghshpour, Shahdad., |
spellingShingle |
Naghshpour, Shahdad., A primer on nonparametric analysis. Economics collection, Section I. One-sample tests -- 1. Goodness of fit tests -- 2. Randomness tests -- 3. One-sample location inference -- Section II. One-sample tests -- 4. Comparing two unrelated samples: the Mann-Whitney U test -- 5. Goodness of fit for two samples -- Index. |
author_facet |
Naghshpour, Shahdad., |
author_variant |
s n sn |
author_role |
VerfasserIn |
author_sort |
Naghshpour, Shahdad., |
title |
A primer on nonparametric analysis. |
title_full |
A primer on nonparametric analysis. Volume I / Shahdad Naghshpour. |
title_fullStr |
A primer on nonparametric analysis. Volume I / Shahdad Naghshpour. |
title_full_unstemmed |
A primer on nonparametric analysis. Volume I / Shahdad Naghshpour. |
title_auth |
A primer on nonparametric analysis. |
title_new |
A primer on nonparametric analysis. |
title_sort |
a primer on nonparametric analysis. |
series |
Economics collection, |
series2 |
Economics collection, |
publisher |
Business Expert Press, |
publishDate |
2016 |
physical |
1 online resource (xxvii, 120 pages) |
edition |
First edition. |
contents |
Section I. One-sample tests -- 1. Goodness of fit tests -- 2. Randomness tests -- 3. One-sample location inference -- Section II. One-sample tests -- 4. Comparing two unrelated samples: the Mann-Whitney U test -- 5. Goodness of fit for two samples -- Index. |
isbn |
9781631574467 9781631574450 |
issn |
2163-7628 |
callnumber-first |
Q - Science |
callnumber-subject |
QA - Mathematics |
callnumber-label |
QA278 |
callnumber-sort |
QA 3278.8 N246 42016 |
genre |
Electronic books. |
genre_facet |
Electronic books. |
url |
https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=4648712 |
illustrated |
Not Illustrated |
dewey-hundreds |
500 - Science |
dewey-tens |
510 - Mathematics |
dewey-ones |
519 - Probabilities & applied mathematics |
dewey-full |
519.5 |
dewey-sort |
3519.5 |
dewey-raw |
519.5 |
dewey-search |
519.5 |
oclc_num |
957588810 |
work_keys_str_mv |
AT naghshpourshahdad aprimeronnonparametricanalysisvolumei AT naghshpourshahdad primeronnonparametricanalysisvolumei |
status_str |
n |
ids_txt_mv |
(MiAaPQ)5004648712 (Au-PeEL)EBL4648712 (CaPaEBR)ebr11249676 (CaONFJC)MIL949214 (OCoLC)957588810 |
hierarchy_parent_title |
Economics collection, |
is_hierarchy_title |
A primer on nonparametric analysis. |
container_title |
Economics collection, |
_version_ |
1792330921692626945 |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>04209nam a2200589 i 4500</leader><controlfield tag="001">5004648712</controlfield><controlfield tag="003">MiAaPQ</controlfield><controlfield tag="005">20200520144314.0</controlfield><controlfield tag="006">m o d | </controlfield><controlfield tag="007">cr cnu||||||||</controlfield><controlfield tag="008">160829s2016 nyu foa 001 0 eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="z">9781631574450</subfield><subfield code="q">paperback</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781631574467</subfield><subfield code="q">(electronic bk.)</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(MiAaPQ)5004648712</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(Au-PeEL)EBL4648712</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CaPaEBR)ebr11249676</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CaONFJC)MIL949214</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)957588810</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">MiAaPQ</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="e">pn</subfield><subfield code="c">MiAaPQ</subfield><subfield code="d">MiAaPQ</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">QA278.8</subfield><subfield code="b">.N246 2016</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">519.5</subfield><subfield code="2">23</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Naghshpour, Shahdad.,</subfield><subfield code="e">author.</subfield></datafield><datafield tag="245" ind1="1" ind2="2"><subfield code="a">A primer on nonparametric analysis.</subfield><subfield code="n">Volume I /</subfield><subfield code="c">Shahdad Naghshpour.</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">First edition.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">New York, New York (222 East 46th Street, New York, NY 10017) :</subfield><subfield code="b">Business Expert Press,</subfield><subfield code="c">2016.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (xxvii, 120 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">Economics collection,</subfield><subfield code="x">2163-7628</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Includes index.</subfield></datafield><datafield tag="505" ind1="0" ind2=" "><subfield code="a">Section I. One-sample tests -- 1. Goodness of fit tests -- 2. Randomness tests -- 3. One-sample location inference -- Section II. One-sample tests -- 4. Comparing two unrelated samples: the Mann-Whitney U test -- 5. Goodness of fit for two samples -- Index.</subfield></datafield><datafield tag="506" ind1="1" ind2=" "><subfield code="a">Access restricted to authorized users and institutions.</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">Nonparametric statistics provide a scientific methodology for cases where customary statistics are not applicable. Nonparametric statistics are used when the requirements for parametric analysis fail, such as when data are not normally distributed or the sample size is too small. The method provides an alternative for such cases and is often nearly as powerful as parametric statistics. Another advantage of nonparametric statistics is that it offers analytical methods that are not available otherwise. In social sciences, often, it is not possible to obtain measurements, which renders customary analysis impossible. For example, it is not possible to measure utility but is possible to rank preference, which is based on the unmeasurable utility. Nonparametric methods provide theoretically valid options for analysis, making the use of unscientific methods unnecessary. Nonparametric methods are intuitive and simple to comprehend, which helps researchers in the social sciences understand the methods in spite of lacking mathematical rigor needed in analytical methods customarily used in science. The only prerequisite for this book is high school level elementary algebra. This book is a methodology book and bypasses theoretical proofs while providing comprehensive explanations of the logic behind the methods and ample examples, which are all solved using direct computations as well as by using Stata. The book is arranged into two integrated volumes. Although each volume, and for that matter each chapter, can be used separately, it is advisable to read as much of both volumes as possible; because familiarity with what is applicable for different problems will enhance capabilities. It is recommended that everyone read the Introduction and Chapter 1 because determining whether data are random or normally distributed is essential in the selection of parametric versus nonparametric methods.</subfield></datafield><datafield tag="588" ind1=" " ind2=" "><subfield code="a">Title from PDF title page (viewed on August 29, 2016).</subfield></datafield><datafield tag="590" ind1=" " ind2=" "><subfield code="a">Electronic reproduction. Ann Arbor, MI : ProQuest, 2016. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Nonparametric statistics.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Nonparametric statistics</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">median</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">order statistics</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">rank</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">one sample</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">two samples</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">several samples</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">multiple comparison</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">normality</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">skewness</subfield></datafield><datafield tag="655" ind1=" " ind2="4"><subfield code="a">Electronic books.</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Print version:</subfield><subfield code="z">9781631574450</subfield></datafield><datafield tag="797" ind1="2" ind2=" "><subfield code="a">ProQuest (Firm)</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">Economics collection.</subfield><subfield code="x">2163-7628</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=4648712</subfield><subfield code="z">Click to View</subfield></datafield></record></collection> |