Lisa Starr
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Lisa Starr
Exhibitfb1-1
Afbscientistfbrandomlyfbdividedfbafbgroupfboffb100fblabfbratsfbintofbtwofbgroupsfboffb50.fbOnefbgroupfbwasfbfed
fbregularfbratfbchowfbwhilefbthefbotherfbwasfbfedfbthefbsamefbamountfboffbratfbchowfbwithfbaddedfbDDT.fbBothf
bgroupsfbwerefbhousedfbinfbthefbsamefbroomfbwithfbthefbsamefbenvironmentalfbconditions.fbAtfbthefbendfboffbt
hefbexperiment,fbratsfbwerefbweighedfbandfbthefbmeanfbdifferencefbcalculated.
28. Referfbtofbthefbaccompanyingfbnarrative.fbWhatfbvariablefborfbvariablesfbwerefbmanipulatedfbbyfbthefbscientist?
a. DDTfbonly
b. temperaturefbonly
c. weightfbdifferencesfbonly
d. bothfbDDTfbandfbweightfbdifferences
e. bothfbtemperaturefbandfbweightfbdifferences
ANSWER: a
POINTS: 1
REFERENCES: Sectionfb1.5fbHowfbdoesfbsciencefbwork?
LEARNINGfbOBJECTIVES: BCA.SES.1.5.3fb-
fbUsingfbafbsuitablefbexample,fbdistinguishfbbetweenfbdependentfbandfbindepe
ndentfbvariables.
KEYWORDS: Bloom's:fbApplyfb|fbAnalyze
29. Referfbtofbthefbaccompanyingfbnarrative.fbWhatfbdependentfbvariablefbwasfbmeasured?
a. DDT
b. temperature
c. weight
d. amountfboffbfood
e. dayfblength
ANSWER: c
POINTS: 1
REFERENCES: Sectionfb1.5fbHowfbdoesfbsciencefbwork?
LEARNINGfbOBJECTIVES: BCA.SES.1.5.3fb-
fbUsingfbafbsuitablefbexample,fbdistinguishfbbetweenfbdependentfbandfbindepe
ndentfbvariables.
KEYWORDS: Bloom's:fbApply
30. Infborderfbtofbreducefbbias,fbscientistsfbusuallyfbpreferfbexperimentsfbthatfbleadfbtofbwhatfbkindfboffbresults?
a. ambiguous
b. imprecise
c. quantitative
d. qualitative
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Lisa Starr
e. subjective
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Lisa Starr
ANSWER: c
REFERENCES: Sectionfb1.7fbWhatfbarefbsomefbpotentialfbpitfallsfbinfbscientificfbinq
uiry?
LEARNINGfbOBJECTIVES: BCA.SES.1.5fb-fbExplainfbthefbscientificfbmethod.
KEYWORDS: Bloom's:fbUnderstand
31. Supposefbthatfbinfbanfbexperiment,fbdifferentfbresultsfbarefbobtainedfbfromfbafbsubsetfbthanfbthefbresults
fbobtainedfbfromfbthefbwhole.fbWhatfbtermfbwouldfbbestfbexplainfbthis?
a. probability
b. trend
c. variable
d. statisticallyfb significant
e. samplingfberror
ANSWER: e
POINTS: 1
REFERENCES: Sectionfb1.7fbWhatfbarefbsomefbpotentialfbpitfallsfbinfbscientificfbinq
uiry?
LEARNINGfbOBJECTIVES: BCA.SES.1.7.2fb-fbHowfbcanfbsamplingfberrorfbbefbminimized?
KEYWORDS: Bloom's:fbUnderstand
NOTES: Modified
32. Anfbexperimenterfbsurveyedfbone-
halffbacrefboffbafbdesertfbpreservefbandfbfoundfbthreefbcactusfbwrenfbnests.fbAssumingfbthatfbthefbhabitatfbisf
bfairlyfbuniform,fbhowfbmanyfbnestsfbwouldfbhefbexpectfbtofbbefbinfbthefbentirefb200-acrefbpreserve?
a. 6
b. 200
c. 600
d. 1200
e. 6000
ANSWER: d
POINTS: 1
REFERENCES: Sectionfb1.7fbWhatfbarefbsomefbpotentialfbpitfallsfbinfbscientificfbinquiry?
LEARNINGfbOBJECTIVES: BCA.SES.1.7.3fb-
fbWhenfbarefbexperimentalfbresultsfbsaidfbtofbbefbstatisticallyfbsignificant?
KEYWORDS: Bloom's:fbApply
33. Anfbexperimentalfbresultfbthatfbisfbstatisticallyfbsignificantfbis:
a. likelyfbtofboccurfbbyfbchancefbalone
b. unlikelyfbtofboccurfbbyfbchancefbalone
c. scientificallyfbsignificantfborfbimportant
d. thefbresultfboffbanfbexperimentfbwithfbonlyfbonefbvariable
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