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WPC 300 Midterm 1 Questions and Answers
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WPC 300 Midterm 1 Questions and Answers
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WPC 300 Midterm 1 Questions andAnswers
Heuristic ii- iiAnswers ii-Learns iiby iiacting, iiuses iitrial iiand iierror, iivalues iiexperiences,
iirelies iion iicommon iisense, iiseeks iisatisfying iisolutions
Analytic ii- iiAnswers ii-Learns iiby iianalyzing, iiuses iistep iiby iistep iiprocedure, iivalues
iiquantitative iiand iimodels, iibuilds iimathematical iimodels, iiseeks iioptimal iisolution
Data iiextraction ii- iiAnswers ii-Extract iidata iifrom iiprimary/secondary iisource
Data iitransformation ii- iiAnswers ii-Transform/clean iidata iiinto iiproper iiformat iior
iistructure iifor iithe iipurpose iiof iiquerying iiand iianalysis
Data iiload ii- iiAnswers ii-Load iidata iiinto iifinal iitarget iidatabase, iimore iispecifically iias
iioperational iidata iistore, iidata iimart iior iidata iiwarehouse
Descriptive iiModeling ii- iiAnswers ii-Basic iiplots iiof iivariables
Find iipatterns iiin iidata
Descriptive iistatistics
Correlations
Outliers
Sampling ii
Some iidata iimining iitechniques ii- iiclustering
Explanatory iimodeling ii- iiAnswers ii-Develop iimodel iito iiunderstand iia ii(causal)
iirelationship
Predictive iianalysis ii- iiAnswers ii-Linear iiregression
Data iimining
Classification
Decision iitree
Association iirule ii(market iibasket iianalysis)
Text iimining
Simulation
Problem iiFraming ii- iiAnswers ii-Tell iian iiinteresting iiand iicomplete iistory, iifind iian
iiappropriate iisolution iiframework, iiroutinize iithe iiprocedure
Agile ii- iiAnswers ii-Empirical iiprocess iicontrol
, Waterfall ii- iiAnswers ii-Defined iiprocess iicontrol
Hypothesis ii- iiAnswers ii-Educated iiGuess
Data ii- iiAnswers ii-Discrete, iiunorganized, iiraw iifacts
Information ii- iiAnswers ii-the iitransformation iiof iithose iifacts iiinto iimeaning
Primary iiData ii- iiAnswers ii-Survey, iiInterviews ii(marketing iifirm's iitelephone iiinterviews),
iiUsed iia iilot iiin iimarketing iiresearch
Secondary iiData ii- iiAnswers ii-Firm's iiproprietary iidatabase, iiInternet iidata ii(crawlers)
ii[scarpy, iibeautifulsoup], iiStock/capital iimarket iidata ii(compustat, iiCRSP), iiAccounting
iidisclosure iidata ii(from ii10k, ii10Q)
Simulated iiData ii- iiAnswers ii-Data iibased iion iiassumption iiand iisimulation, iiUsed iia iilot
iiin iischeduling, iirouting iiand iiqueuing
Descriptive iiData iiAnalysis ii- iiAnswers ii-What iihappened? iiWhy iiis iiit iihappening?,
iioutcomes iiare iiwell-defined iibusiness iiproblems iiand iiopportunities
predictive iidata iianalytics ii- iiAnswers ii-What iiwill iihappen? iiWhy iiwill iiit iihappen?
iiOutcomes iiare iiaccurate iiprojections iiof iifuture iievents iiand iioutcomes
Prescriptive iiData iiAnalysis ii- iiAnswers ii-What iishould iiI iido iiand iiwhy? iiOutcomes iiare
iibest iipossible iibusiness iidecisions iiand iiactions
Explanatory iiModeling ii- iiAnswers ii-Develop iimodel iito iiunderstand iia ii(causal)
iirelationship
Science ii- iiAnswers ii-The iiintellectual iiand iipractical iiactivity iiencompassing iithe
iisystematic iistudy iiof iithe iistructure iiand iibehavior iiof iithe iiphysical iiand iinatural iiworld
iithrough iiobservation iiand iiexperiments
Social iiscience ii- iiAnswers ii-major iicategory iiof iiacademic iidisciplines, iiconcerned iiwith
iisociety iiand iirelationships iiamong iiindividuals iiwithin iia iisociety
observational iistudy ii- iiAnswers ii-social iiscientists iiobserve iisubjects iiand iimeasure
iivariables iiof iiinterest iiwithout iiassigning iitreatments iito iisubjects
experimental iistudy ii- iiAnswers ii-you iiapply iitreatment iito iiexperimental iiunits ii(people,
iianimals, iihospitals iietc.) iiand iithen iiobserve iithe iieffects iiof iithe iitreatments iion iithe
iiexperimental iiunits
Analytics ii- iiAnswers ii-The iidiscovery, iiinterpretation, iiand iicommunication iiof
iimeaningful iipatterns iiin iidata
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