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Quantitative Research & Statistics Exam Q&A, Exams of Nursing

University of Iowa (UI)Nursing

A compilation of questions and answers related to quantitative research techniques and statistics, specifically tailored for the peregrine exam. It covers a range of topics including sampling methods, probability, statistical inference, hypothesis testing, and measures of central tendency and variability. The material is presented in a question-and-answer format, making it useful for exam preparation and review. It includes definitions of key statistical concepts and examples to illustrate their application. Designed to help students understand and apply statistical principles in research contexts, focusing on practical knowledge and problem-solving skills. It is a valuable resource for students preparing for exams or seeking to reinforce their understanding of quantitative methods. The content is structured to facilitate quick review and comprehension, making it an effective study aid for mastering statistical concepts and techniques.

Typology: Exams

2024/2025

Available from 06/12/2025

Nurseexcel
Nurseexcel 🇺🇸

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Quantitative Research Techniques + Statistics – Peregrine Exam
Questions and Answers Graded A+
1. Avcompanyvdevelopedvavsmartphonevwhosevaveragevlifetimevisvunknown.vInvordervtovesti
matevthevaverage,v200vsmartphonesvarevrandomlyvselectedvfromvavlargevproductionvlinevan
dvtested;vtheirvaveragevisvfoundvtovbev5vyears.vThev200vsmartphonesvrepresent::vavsample
2. Significancevlevel:vMeasuresvthevreliabilityvofvavstatisticalvinference
3. inferentialvstatistics:vProcessvofvusingvsamplevstatisticsv(mathematics)vtovdrawvconclusio
nsvaboutvpopulationvparameters
4. mutuallyvexclusive:vEventsvthatvcannotvoccurvatvthevsamevtime.
5. samplingverror:vthevdifferencevbetweenvthevresultsvofvrandomvsamplesvtakenvatvthevsamevt
ime
6. non-
samplingverror:voccursvwhenvthevsamplevdatavarevincorrectlyvcollected,vrecorded,vorvanalyze
d.vThreevtypesvofverrors:vdatavacquisitionverrors,vnon-responseverrorsv(orvbias),vselectionvbias
7. Designvofvavgoodvsurveyvcomponents:vshortvsurvey,vshort/simplevquestions,vstartvwithvd
emographicvquestions,vuesvdichtomousv(yes-no)vandvmultiplevchoice
8. Directvobservation:vexample:vcountsvbackpacksvonvcampusvforvavday
9. stratifiedvrandomvsample:vavsamplevfromvselectedvsubgroupsvofvthevtargetvpopulationv
invwhichveveryonevinvthosevsubgroupsvhasvanvequalvchancevofvbeingvincludedvinvthevresear
ch
example:vThevmanagervofvavcustomervservicevdivisionvwantsvtovknowvifvthevcustomersvinvthevpastv1
2vmonthsvarevsatisfiedvwithvtheirvpurchasevofvCD's.vTherevarevfourvtypesvofvCD's.
10. JointvProbability:vthevprobabilityvofvthevintersectionvofvtwovevents
11. Unionvofvtwovevents:vThevunionvofveventsvAvandvBvisvtheveventvcontainingvallvsamplevpoin
tsvthatvarevinvAvorvBvorvboth
12. MarginalvProbability:vthevprobabilityvofvavsingleveventvwithoutvconsiderationvofvanyvotherv
event
13. ConditionalvProbability:vthevlikelihoodvthatvavtargetvbehaviorvwillvoccurvinvavgivenvcirc
pf3
pf4
pf5

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Quantitative Research Techniques + Statistics – Peregrine Exam

Questions and Answers Graded A+

  1. Avcompanyvdevelopedvavsmartphonevwhosevaveragevlifetimevisvunknown.vInvordervtovesti matevthevaverage,v 200 vsmartphonesvarevrandomlyvselectedvfromvavlargevproductionvlinevan dvtested;vtheirvaveragevisvfoundvtovbev 5 vyears.vThev 200 vsmartphonesvrepresent::v avsample
  2. Significancevlevel:v Measuresvthevreliabilityvofvavstatisticalvinference
  3. inferentialvstatistics:v Processvofvusingvsamplevstatisticsv(mathematics)vtovdrawvconclusio nsvaboutvpopulationvparameters
  4. mutuallyvexclusive:v Eventsvthatvcannotvoccurvatvthevsamevtime.
  5. samplingverror:v thevdifferencevbetweenvthevresultsvofvrandomvsamplesvtakenvatvthevsamevt ime
  6. non- samplingverror:v occursvwhenvthevsamplevdatavarevincorrectlyvcollected,vrecorded,vorvanalyze d.vThreevtypesvofverrors:vdatavacquisitionverrors,vnon-responseverrorsv(orvbias),vselectionvbias
  7. Designvofvavgoodvsurveyvcomponents:v shortvsurvey,vshort/simplevquestions,vstartvwithvd emographicvquestions,vuesvdichtomousv(yes-no)vandvmultiplevchoice
  8. Directvobservation:v example:vcountsvbackpacksvonvcampusvforvavday
  9. stratifiedvrandomvsample:v avsamplevfromvselectedvsubgroupsvofvthevtargetvpopulationv invwhichveveryonevinvthosevsubgroupsvhasvanvequalvchancevofvbeingvincludedvinvthevresear ch example:vThevmanagervofvavcustomervservicevdivisionvwantsvtovknowvifvthevcustomersvinvthevpastv 1 2 vmonthsvarevsatisfiedvwithvtheirvpurchasevofvCD's.vTherevarevfourvtypesvofvCD's.
  10. JointvProbability:v thevprobabilityvofvthevintersectionvofvtwovevents
  11. Unionvofvtwovevents:v ThevunionvofveventsvAvandvBvisvtheveventvcontainingvallvsamplevpoin tsvthatvarevinvAvorvBvorvboth
  12. MarginalvProbability:v thevprobabilityvofvavsingleveventvwithoutvconsiderationvofvanyvotherv event
  13. ConditionalvProbability:v thevlikelihoodvthatvavtargetvbehaviorvwillvoccurvinvavgivenvcirc

umstance

  1. BayesvLaw:v calculatesvposteriorvprobability
  2. exhaustive:v includingveverythingvpossible;vveryvthoroughvorvcomplete
  3. CentralvLimitvTheoremv(CLT):v Thevnamevofvthevtheoremvstatingvthatvthevsam- vplingvdistributionvofvavstatisticv(e.g.vxv)visvapproximatelyvnormalvwhenevervthevsamplevisvlargevan dvrandom.vAllowsvusvtovdrawvconclusionsvaboutvthevpopulationvbasedvonvstrictlyvsamplevdata.
  4. samplingvdistributionvofvthevmean:v 1.vthevsamplingvdistributionvofvthevmeanvhasvavdiffer entvmeanvfromvthevoriginalvpopulation
  5. thevstandardvdeviationvofvthevsamplingvdistributionvofvthevmeanvisvreferredvtovas

hevfinitevpopulationvcorrectionvfactor

  1. Invavsamplevproportion,vrepresentedvbyvpv=vx/n,vwhatvdoesvXvrefervto?:v #vofvsuccessesvinv thevsample
  2. Thevbranchesvinvavdecisionvtreevarevequivalentvto:v eventsvandvacts
  3. Whatvisvneededvtovcomputevposteriorvprobabilities?:v ThevsumvofvallvthevP(sjvandvli)'s,vlike lihoodvprobabilities,vpv(li/sj)
  1. doingvinferentialvstatistics.:v Thevprocessvofvusingvsamplevstatisticsvtovdrawvconclusio nsvaboutvpopulationvparametersvisvcalled
  2. Thevconfidencevlevel:v measuresvthevproportionvofvtimesvanvestimationvproce- vdurevwillvbevcorrectvinvthevlongvrun
  3. Parameter:v avsummaryvmeasurevthatvisvcomputed
  4. samplevspace:v thevsetvofvallvpossiblevoutcomesvofvavprobabilityvexperiment
  5. priorvprobabilities:v initialvestimatesvofvthevprobabilitiesvofvevents
  6. thevstandardverrorvofvthevsamplevmean:v standardvdeviationvofvthevdistributionvofvthevsam plevmeansv,vStandardvdeviation/sqvrtv(populationvsize)
  7. BusinessvStatistics:v thevcollection,vsummarization,vanalysis,vandvreportingvofvnumerical vfindingsvrelevantvtovavbusinessvdecisionvorvsituation
  8. descriptivevstatistics:v usesvgraphicalvorvnumericalvtechniquesvtovsummarizevandvprese ntvdata
  9. mean:v average
  10. measurevofvvariability:v howvcloselyvscoresvbunchvupvaroundvthevcentralvpoint;vavstatisticv thatvindicatesvthevspreadvofvdistribution
  11. range:v thevdifferencevbetweenvthevhighestvandvlowestvscoresvinvavdistribution
  12. Median:v thevmiddlevscorevinvavdistribution;vhalfvthevscoresvarevabovevitvandvhalfvarevbelowvi t
  13. Mode:v thevmostvfrequentlyvoccurringvscore(s)vinvavdistribution
  14. Variance:v thevaveragevofvthevsquaredvdeviationsvfromvthevmean
  15. standardvdeviation:v thevsquarevrootvofvthevvariancevandvprovidesvavmeasurevofvthevstandar d,vorvaverage,vdistancevfromvthevmean
  16. Threevconceptsvthatvavstatisticalvinferencevproblemvcontains:v thevpopula- vtion,vthevsample,vandvthevstatisticalvinference
  17. Parameter:v avdescriptivevmeasurevofvavpopulation
  18. statistic:v avnumbervthatvdescribesvavsample
  19. statisticalvinference:v processvofvmakingvanvestimate,vprediction,vorvdecisionvaboutvavp opulationvbasedvonvavsample
  20. confidencevlevel:v Proportionvofvtimesvthatvanvestimatingvprocedurevwillvbevcorrect
  21. Confidencevlevelv+vsignificancevlevel:v =v 1

nevorvtovboth

  1. clustervsampling:v randomvsamplevofvthevgroupsvorvclustersvofvelementsvversusvavsimplevra ndomvsamplevofvindividualvobjects
  2. Probabilityvofvanyvoutcomevmustvbevbetween:v 0 vandv 1
  3. Sumvofvallvprobabilitiesvmustvequal:_____________ 1
  4. Threevapproachesvtovassigningvprobability:v classicalvapproach,vrelativevfre- vquencyvapproach,vsubjectivevapproach
  5. ClassicalvApproachvtovProbability:v associatedvwithvgamesvofvchance.vIfvanvexperimentvh asvNvpossiblevoutcomes,vthisvmethodvwouldvassignvprobabilityvofv1/nvtoveachvcustomer.vForvexa mple,vthevprobabilityvofvavheadsvandvtailsvinvthevflipvofvavcoinvarevequalvtoveachvother.vBecausevt hevsumvmustvbev1,vthevprobabilityvisv1/2,vorv1/6vforvavdice.
  6. relativevfrequencyvapproachvtovprobability:v definesvprobabilityvasvthevlongvrunvfrequenc yvinvwhichvsomethingvoccurs.vExample:vthevlastv 1000 vstudentsvtookvavcourse,v 200 vgotvanvA.vTh evrelativevfrequencyvisv20%v-vestimatevofvstudentsvthatvwillvgetvanvA
  7. subjectivevapproachvtovprobability:v thevprobabilityvisvobtainedvonvthevbasisvofvpersonalvju dgement;voftenvthevonlyvmethodvofvassigningvlikelihoodvtovanvoutcome;veducatedvguessvbase dvonvknowledgevavailable
  8. unionvofvtwovevents:v Givenvbyvthevoutcomesvthatvbelongveithervtovovevents.
  9. calculatevconditionalvProbability:v Pv(A1/B2)
  10. ComplementvProbability:v eventvthatvoccursvwhenvAvdoesvnotvoccur.vP(A)v+vP(Ac)v=v 1
  11. multiplicationvrule:v Tovdeterminevthevprobability,vwevmultiplyvthevprobabilityvofvonevevent vbyvthevprobabilityvofvanother.
  12. AdditionvRulevofvProbability:v P(AvorvB)v=vP(A)v+vP(B)v-vP(AB)
  13. standardverror:v thevstandardvdeviationvofvavsamplingvdistribution
  14. Complementvofvanvevent: