TEST BANK x x
Introduction to Statistical Investigations,
x x x x
2nd Edition Nathan Tintle; Beth L. Chance
x x x x x x
x Chapters 1 - 11, Complete
x x x x
FOR xINSTRUCTOR xUSE
xONLY
,TABLE OF CONTENTS
x x x
Chapter 1 – Significance: How Strong is the Evidence
x x x x x x x x x
Chapter 2 – Generalization: How Broadly Do the Results
x x x x x x x x
x Apply? x
Chapter 3 – Estimation: How Large is the Effect?
x x x x x x x x x
Chapter 4 – Causation: Can We Say What Caused the Effect?
x x x x x x x x x x x
Chapter 5 – Comparing Two Proportions
x x x x x x
Chapter 6 – Comparing Two Means
x x x x x x
Chapter 7 – Paired Data: One Quantitative Variable
x x x x x x x x
Chapter 8 – Comparing More Than Two Proportions
x x x x x x x x
Chapter 9 – Comparing More Than Two Means
x x x x x x x x
Chapter 10 – Two Quantitative Variables
x x x x x x
Chapter 11 – Modeling Randomness
x x x x
FOR xINSTRUCTOR xUSE
xONLY
,Chapter 1 x
Note: x x xTE x = x Text xentry TE-N x= xText xentry x- xNumeric
Ma x =
x x Matching MS x = x Multiple xselect
MC x = x Multiple xchoice TF x= xTrue-FalsexE
x = xEasy, xM x= xMedium, xH x= xHard
CHAPTER 1 LEARNING OBJECTIVES
x x x
CLO1-1: xUse xthe xchance xmodel xto xdetermine xwhether xan xobserved xstatistic xis xunlikely xto xoccur.
CLO1-2: xCalculate xand xinterpret xa xp-value, xand xstate xthe xstrength xof xevidence xit xprovides xagainstxthe
xnull xhypothesis.
CLO1-3: xCalculate xa xstandardized xstatistic xfor xa xsingle xproportion xand xevaluate xthe xstrength xof
xevidence x it xprovides xagainst xa xnull xhypothesis.
CLO1-4: xDescribe xhow xthe xdistance xof xthe xobserved xstatistic xfrom xthe xparameter xvalue xspecifiedxby
xthe xnull xhypothesis, xsample x size, xand xone- xvs. xtwo-sided x tests xaffect xthe xstrength x of
xevidence x against xthe x null xhypothesis.
CLO1-5: xDescribe xhow xto xcarry xout xa xtheory-based, xone-proportion xz-test.
Section 1.1: Introduction to Chance Models
x x x x x
LO1.1-1: xRecognize xthe xdifference xbetween xparameters xand xstatistics.
LO1.1-2: xDescribe xhow xto xuse xcoin xtossing xto xsimulate xoutcomes xfrom xa xchance xmodel xof xthe xran-
xdom xchoice x between x two x events.
LO1.1-3: xUse xthe xOne xProportion xapplet xto xcarry xout xthe xcoin xtossing xsimulation.
LO1.1-4: xIdentify xwhether xor xnot xstudy xresults xare xstatistically xsignificant xand xwhether xor xnot xthe
xchance x model xis xa x plausible xexplanation xfor xthe xdata.
LO1.1-5: xImplement xthe x3S xstrategy: xfind xa xstatistic, xsimulate xresults xfrom xa xchance xmodel, xand
xcomment xon xstrength xof xevidence xagainst xobserved xstudy xresults xhappening xby xchance
xalone.
LO1.1-6: xDifferentiate xbetween xsaying xthe xchance xmodel xis xplausible xand xthe xchance xmodel xis xthe
xcorrect xexplanation xfor xthe xobserved xdata.
FOR xINSTRUCTOR xUSE
xONLY
, 1-2 Test xBank xfor xIntroduction xto xStatistical xInvestigations, x2nd xEdition
Questions x1 xthrough x4:
Do xred xuniform xwearers xtend xto xwin xmore xoften xthan xthose xwearing xblue xuniforms xin
xTaekwondo xmatches xwhere xcompetitors xare xrandomly xassigned xto xwear xeither xa xred xor
xblue xuniform? xIn xa xsample xof x80 xTaekwondo xmatches, xthere xwere x45 xmatches xwhere xthe
xred xuniform xwearer xwon.
1. What xis xthe xparameter xof xinterest xfor xthis xstudy?
A. The xlong-run xproportion xof xTaekwondo xmatches xin xwhich xthe xred xuniform xwearer
xwins
B. The xproportion xof xmatches xin xwhich xthe xred xuniform xwearer xwins xin xa xsample xof
x80xTaekwondo x matches
C. Whether xthe xred xuniform xwearer xwins xa xmatch
D. x 0.50
Ans: xA; xLO: x1.1-1; xDifficulty: xEasy; xType: xMC
2. What xis xthe xstatistic xfor xthis xstudy?
A. The xlong-run xproportion xof xTaekwondo xmatches xin xwhich xthe xred xuniform xwearer
xwins
B. The xproportion xof xmatches xin xwhich xthe xred xuniform xwearer xwins xin xa xsample xof
x80xTaekwondo x matches
C. Whether xthe xred xuniform xwearer xwins xa xmatch
D. x 0.50
Ans: xB; xLO: x1.1-1; xDifficulty: xEasy; xType: xMC
3. Given xbelow xis xthe xsimulated xdistribution xof xthe xnumber xof x―red xwins‖ xthat xcould xhappen
xby xchance xalone xin xa xsample xof x80 xmatches. xBased xon xthis xsimulation, xis xour xobserved
xresult xstatistically xsignificant?
A. Yes, xsince x45 xis xlarger xthan x40.
B. Yes, xsince xthe xheight xof xthe xdotplot xabove x45 xis xsmaller xthan xthe xheight xof
xthexdotplot xabove x40.
C. No, xsince x45 xis xa xfairly xtypical xoutcome xif xthe xcolor xof xthe xwinner‘s xuniform
FOR xINSTRUCTOR xUSE
xONLY
Introduction to Statistical Investigations,
x x x x
2nd Edition Nathan Tintle; Beth L. Chance
x x x x x x
x Chapters 1 - 11, Complete
x x x x
FOR xINSTRUCTOR xUSE
xONLY
,TABLE OF CONTENTS
x x x
Chapter 1 – Significance: How Strong is the Evidence
x x x x x x x x x
Chapter 2 – Generalization: How Broadly Do the Results
x x x x x x x x
x Apply? x
Chapter 3 – Estimation: How Large is the Effect?
x x x x x x x x x
Chapter 4 – Causation: Can We Say What Caused the Effect?
x x x x x x x x x x x
Chapter 5 – Comparing Two Proportions
x x x x x x
Chapter 6 – Comparing Two Means
x x x x x x
Chapter 7 – Paired Data: One Quantitative Variable
x x x x x x x x
Chapter 8 – Comparing More Than Two Proportions
x x x x x x x x
Chapter 9 – Comparing More Than Two Means
x x x x x x x x
Chapter 10 – Two Quantitative Variables
x x x x x x
Chapter 11 – Modeling Randomness
x x x x
FOR xINSTRUCTOR xUSE
xONLY
,Chapter 1 x
Note: x x xTE x = x Text xentry TE-N x= xText xentry x- xNumeric
Ma x =
x x Matching MS x = x Multiple xselect
MC x = x Multiple xchoice TF x= xTrue-FalsexE
x = xEasy, xM x= xMedium, xH x= xHard
CHAPTER 1 LEARNING OBJECTIVES
x x x
CLO1-1: xUse xthe xchance xmodel xto xdetermine xwhether xan xobserved xstatistic xis xunlikely xto xoccur.
CLO1-2: xCalculate xand xinterpret xa xp-value, xand xstate xthe xstrength xof xevidence xit xprovides xagainstxthe
xnull xhypothesis.
CLO1-3: xCalculate xa xstandardized xstatistic xfor xa xsingle xproportion xand xevaluate xthe xstrength xof
xevidence x it xprovides xagainst xa xnull xhypothesis.
CLO1-4: xDescribe xhow xthe xdistance xof xthe xobserved xstatistic xfrom xthe xparameter xvalue xspecifiedxby
xthe xnull xhypothesis, xsample x size, xand xone- xvs. xtwo-sided x tests xaffect xthe xstrength x of
xevidence x against xthe x null xhypothesis.
CLO1-5: xDescribe xhow xto xcarry xout xa xtheory-based, xone-proportion xz-test.
Section 1.1: Introduction to Chance Models
x x x x x
LO1.1-1: xRecognize xthe xdifference xbetween xparameters xand xstatistics.
LO1.1-2: xDescribe xhow xto xuse xcoin xtossing xto xsimulate xoutcomes xfrom xa xchance xmodel xof xthe xran-
xdom xchoice x between x two x events.
LO1.1-3: xUse xthe xOne xProportion xapplet xto xcarry xout xthe xcoin xtossing xsimulation.
LO1.1-4: xIdentify xwhether xor xnot xstudy xresults xare xstatistically xsignificant xand xwhether xor xnot xthe
xchance x model xis xa x plausible xexplanation xfor xthe xdata.
LO1.1-5: xImplement xthe x3S xstrategy: xfind xa xstatistic, xsimulate xresults xfrom xa xchance xmodel, xand
xcomment xon xstrength xof xevidence xagainst xobserved xstudy xresults xhappening xby xchance
xalone.
LO1.1-6: xDifferentiate xbetween xsaying xthe xchance xmodel xis xplausible xand xthe xchance xmodel xis xthe
xcorrect xexplanation xfor xthe xobserved xdata.
FOR xINSTRUCTOR xUSE
xONLY
, 1-2 Test xBank xfor xIntroduction xto xStatistical xInvestigations, x2nd xEdition
Questions x1 xthrough x4:
Do xred xuniform xwearers xtend xto xwin xmore xoften xthan xthose xwearing xblue xuniforms xin
xTaekwondo xmatches xwhere xcompetitors xare xrandomly xassigned xto xwear xeither xa xred xor
xblue xuniform? xIn xa xsample xof x80 xTaekwondo xmatches, xthere xwere x45 xmatches xwhere xthe
xred xuniform xwearer xwon.
1. What xis xthe xparameter xof xinterest xfor xthis xstudy?
A. The xlong-run xproportion xof xTaekwondo xmatches xin xwhich xthe xred xuniform xwearer
xwins
B. The xproportion xof xmatches xin xwhich xthe xred xuniform xwearer xwins xin xa xsample xof
x80xTaekwondo x matches
C. Whether xthe xred xuniform xwearer xwins xa xmatch
D. x 0.50
Ans: xA; xLO: x1.1-1; xDifficulty: xEasy; xType: xMC
2. What xis xthe xstatistic xfor xthis xstudy?
A. The xlong-run xproportion xof xTaekwondo xmatches xin xwhich xthe xred xuniform xwearer
xwins
B. The xproportion xof xmatches xin xwhich xthe xred xuniform xwearer xwins xin xa xsample xof
x80xTaekwondo x matches
C. Whether xthe xred xuniform xwearer xwins xa xmatch
D. x 0.50
Ans: xB; xLO: x1.1-1; xDifficulty: xEasy; xType: xMC
3. Given xbelow xis xthe xsimulated xdistribution xof xthe xnumber xof x―red xwins‖ xthat xcould xhappen
xby xchance xalone xin xa xsample xof x80 xmatches. xBased xon xthis xsimulation, xis xour xobserved
xresult xstatistically xsignificant?
A. Yes, xsince x45 xis xlarger xthan x40.
B. Yes, xsince xthe xheight xof xthe xdotplot xabove x45 xis xsmaller xthan xthe xheight xof
xthexdotplot xabove x40.
C. No, xsince x45 xis xa xfairly xtypical xoutcome xif xthe xcolor xof xthe xwinner‘s xuniform
FOR xINSTRUCTOR xUSE
xONLY
