Nonparametric Statistics for Applied Research

416 Pages·2014·9.07 MB·English

by  Jared A. Linebach

Jared A. Linebach · Brian P. Tesch
Lea M. Kovacsiss
Nonparametric
Statistics
for Applied
Research
Nonparametric Statistics for Applied Research

Jared A. Linebach (cid:129) Brian P. Tesch
Lea M. Kovacsiss
Nonparametric Statistics
for Applied Research
JaredA.Linebach BrianP.Tesch
ClearwaterChristianCollege SuffolkUniversity
Clearwater,FL,USA Dover,NewHampshire,USA
LeaM.Kovacsiss
EastCanton,OH,USA
ISBN978-1-4614-9040-1 ISBN978-1-4614-9041-8(eBook)
DOI10.1007/978-1-4614-9041-8
SpringerNewYorkHeidelbergDordrechtLondon
LibraryofCongressControlNumber:2013950181
©SpringerScience+BusinessMediaNewYork2014
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WearemostgratefultoDr.DebraBekerian,Ph.D.,
for her unwavering commitment to us and
the process. Without her guidance and
encouragement, this would never have been
possible. To you, we dedicate this work.

Preface
Ihavebeenworkingasanappliedpsychologistformanyyears,andthereareafew
things that have consistently stood out, for me at least, in the course of my
experiences. Possibly the single, most constant “truth” is that human behavior is
messy. It’s messy in all sorts of interesting ways, and most of the time, people’s
messiness also messes with any type of inference you can make about their
behavior.So,peoplemaynotbehave,asagroup,inanormallydistributedfashion,
orasa“singlehumpedcamel,”astheauthorssayinthisbook.
In fact, applied research is messy. For example, take how you get participants.
You put out feelers, such as links on various websites; you advertise you need
participantsforastudyonwhateveritisyouhappentobestudying.Theindividual
decidestorespondornot—astheresearcher,youprettymuchhavetotakewhoyou
canget.Youalsodon’talwayshavetheopportunitytousemeasurementsthatyou’d
like.So,youmaybereducedtoaskingyes/noquestions,simplybecauseyoucannot
passanethicsboard,peoplewouldn’tanswerthequestionsyoureallywanttoask
orboth.
And, ofcourse, whenyou’re dealing withmessybehavior,there isn’t always a
nice, tidy way of determining whether you’ve found anything significant. That’s
right;I’mtalkingaboutparametricstatistics.Intherealworld,theparametersareso
oftenviolatedthatyouneedtofindanotherway.
To this end, nonparametric statistics offer a delightful smorgasbord of alterna-
tivesfromwhichtosample.Nomatterhowsloppy,nomatterhowimprecise,and
nomatterhowadhocthebehavioralmeasurement,nonparametricstatisticsprom-
ise some light at the end of the tunnel, a way to assess whether your findings are
potentiallypointingtosomethingsignificant.
Whilethereareanumberoftextbooksonnonparametricstatistics,noneofthem
offerswhatthisbookdoes.Thisbookisuniqueinanumberofways.Forone,the
text provides a context for statistical questions: there are applied problems that
drivetheanalyses,andtheproblemsarelinkedtoeachothersothatthereadergetsa
real appreciation of how applied science works. The data set used by the book is
consistent, too. What this means is that the reader is allowed to become familiar,
and confident, with one set of numbers, rather than changing each data set with a
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viii Preface
new statistical test (the traditional statistics book approach). Also unusual and
highly valuable is the decision tree for tests of differences and of association.
I am convinced that these trees will facilitate the problem solving process for
studentsofpsychologyaswellasseasonedresearchers.
The book also departs from the standard in that it provides the reader with a
narrative of real people, doing real things and interacting with each other in real
ways. The issues are real, the consequencesserious. The reader is introduced toa
contextinwhichstatisticsgetapplied,andasaconsequence,therationaleforusing
a test is grounded in an understandable example. This is in stark contrast to the
standard,abstract,detachedexamplesnormallyprovidedinstatisticsbooks.
I am most fortunate to have known these three authors for a few years now.
Ihaveworkedwiththemallonmanyprojectsandhavehadthegoodfortunetosit
for many hours, discussing all manner of things with them. They have produced
abookthatwillnotonlyeducateyoubutalsogiveyouagoodread.
BonAppe´tit!
DebraBekerian
Acknowledgments
Wewouldliketotaketheopportunitytoexpressourgratitudetothemanypeople
whohavehelpedmakethisbookpossible.
Wewouldliketothankallofourfamily,friends,andlovedoneswhopatiently
supportedusasweworkedonthisbook.Theirloveandsupporthelpedustomake
thispossibleandforthatweareforevergrateful.
We would also like to thank Kristin Rodgers, MLIS, Collects Curator, The
MedialHeritageCenteroftheHealthSciencesLibraryattheOhioStateUniversity,
Columbus,Ohio,forassistancewithstatisticaltablesandpermissionsandDanBell,
Ph.D., Associate Professor of Mathematics, School of Arts and Sciences, Tiffin
University,Tiffin,Ohio,foradviceandsupport.
Finally,wewouldliketothankMarcStrauss,HannahBracken,andtheeditorial
staffatSpringerScienceandBusinessMediafortheirguidanceandexpertise.This
bookwouldnothavebeenpossiblewithouttheirbeliefinourwork.
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