Excel in Statistics with the Official Test Bank!
Prepare for exams with this comprehensive test bank for "Introduction to Statistical Investigations," 2nd Edition by Nathan Tintle, Beth L. Chance, and colleagues. This essential study resource contains hundreds of exam-style questions covering ALL 11 chapters, complete with detailed answer keys to help you master statistical concepts, develop investigative skills, and ace your courses.
What's Included:
Complete Coverage of All 11 Chapters:
Chapter 1: Significance: How Strong is the Evidence? – Parameters vs. statistics, 3S strategy (statistic, simulate, strength of evidence), p-values, standardized statistics, null vs. alternative hypotheses, one-proportion z-test, factors affecting strength of evidence (distance from null, sample size, one-sided vs. two-sided tests), theory-based inference for a single proportion
Chapter 2: Generalization: How Broadly Do the Results Apply? – Random sampling, sampling distributions for proportions and means, bias, simulation-based and theory-based tests for a single mean, bootstrap sampling distributions, standard error, Central Limit Theorem, t-distribution, one-sample t-test, validity conditions
Chapter 3: Estimation: How Large is the Effect? – Confidence intervals via repeated tests, 2SD method, theory-based confidence intervals for proportions and means, margin of error, confidence level interpretation, factors affecting interval width (sample size, confidence level, variability), coverage probability, practical vs. statistical significance
Chapter 4: Causation: Can We Say What Caused the Effect? – Conditional proportions, association vs. causation, explanatory vs. response variables, confounding variables, observational studies vs. randomized experiments, random assignment, random sampling, blocking, matched pairs design, cause-and-effect conclusions
Chapter 5: Comparing Two Proportions – Two-way tables, conditional proportions, segmented bar charts, relative risk, 3S strategy for two proportions, simulation-based tests, standardized statistic, 2SD confidence intervals, theory-based tests (z-test) for two proportions, validity conditions, scope of inference
Chapter 6: Comparing Two Means – Describing quantitative distributions (shape, center, variability, outliers), boxplots, comparing means and medians, 3S strategy for two means, simulation-based tests, standardized statistic, 2SD confidence intervals, theory-based tests (t-test) for two means, pooled vs. unpooled procedures, validity conditions
Chapter 7: Paired Data: One Quantitative Variable – Paired designs (repeated measures vs. matching), independent groups vs. paired data, simulation-based analysis of paired differences, theory-based paired t-test, confidence intervals for mean difference, validity conditions
Chapter 8: Comparing More Than Two Proportions – Multiple comparisons and Type I error, Mean Group Diff (MGD) statistic, simulation-based chi-square tests, theory-based chi-square test of association, chi-square statistic, expected counts, validity conditions, follow-up analysis, goodness-of-fit tests
Chapter 9: Comparing More Than Two Means – Mean Group Diff statistic for multiple means, simulation-based ANOVA, theory-based ANOVA (F-test), F-statistic, variability between vs. within groups, validity conditions, follow-up tests, multiple comparisons
Chapter 10: Two Quantitative Variables – Scatterplots (direction, form, strength), correlation coefficient (r), properties of correlation, least-squares regression line, slope and intercept interpretation, predictions and extrapolation, residuals, coefficient of determination (R²), influential points, simulation-based inference for correlation and slope, theory-based inference for slope (t-test), confidence intervals for slope, validity conditions
Chapter 11: Modeling Randomness – Probability basics, sample spaces, equally likely outcomes, probability rules (complement, addition), mutually exclusive events, conditional probability, independence, multiplication rule, tree diagrams, discrete random variables, probability distributions, expected value, variance, standard deviation, linear transformations of random variables, binomial distribution, geometric distribution, normal distribution, empirical rule, z-scores, percentiles, normal approximation to sampling distributions
Question Formats Included:
Multiple choice questions (with answers)
True/False questions (with answers)
Fill-in-the-blank and text entry questions
Matching questions
Multiple select questions
Numerical problems with complete solutions
Applet-based simulation exercises
Data analysis and interpretation questions
Perfect For:
Exam preparation and practice
Understanding statistical concepts through investigation
Developing statistical reasoning and critical thinking
Mastering hypothesis testing and confidence intervals
Self-assessment and study groups
Professors creating course materials
Introductory statistics courses (undergraduate and AP Statistics)
Why Choose This Test Bank?
This comprehensive test bank mirrors the actual exam formats used in university courses. With hundreds of practice questions, simulation exercises, and complete answer keys, you can test your knowledge, identify weak areas, and build confidence before exam day. The questions are organized by textbook chapter, making it easy to review specific topics and concepts.
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TEST BANK k k
Introduction to Statistical Investigations,
k k k k
2nd Edition Nathan Tintle; Beth L. Chance
k k k k k k
Chapters 1 - 11, Complete
k k k k k
FORkINSTRUCTORkUSEkONLY
,TABLE OF CONTENTS
k k k
Chapter 1 – Significance: How Strong is the Evidence
k k k k k k k k k
Chapter 2 – Generalization: How Broadly Do the Results Apply?
k k k k k k k k k k
Chapter 3 – Estimation: How Large is the Effect?
k k k k k k k k k
Chapter 4 – Causation: Can We Say What Caused the Effect?
k k k k k k k k k k k
Chapter 5 – Comparing Two Proportions
k k k k k k
Chapter 6 – Comparing Two Means
k k k k k k
Chapter 7 – Paired Data: One Quantitative Variable
k k k k k k k k
Chapter 8 – Comparing More Than Two Proportions
k k k k k k k k
Chapter 9 – Comparing More Than Two Means
k k k k k k k k
Chapter 10 – Two Quantitative Variables
k k k k k k
Chapter 11 – Modeling Randomness
k k k k
FORkINSTRUCTORkUSEkONLY
,Chapter 1 k
Note:kkkTEk =k Textkentry TE-Nk=kTextkentryk-
kNumerickMak =k Matching MSk =k Multiplekselect
MCk =k Multiplekchoice TFk=kTrue-
FalsekEk=kEasy,kMk=kMedium,kHk=kHard
CHAPTER 1 LEARNING OBJECTIVES
k k k
CLO1-1:kUsekthekchancekmodelktokdeterminekwhetherkankobservedkstatistickiskunlikelyktokoccur.
CLO1-2:kCalculatekandkinterpretkakp-
value,kandkstatekthekstrengthkofkevidencekitkprovideskagainstktheknullkhypothesis.
CLO1-
3:kCalculatekakstandardizedkstatistickforkaksinglekproportionkandkevaluatekthekstrengthkofkeviden
cekitkprovideskagainstkaknullkhypothesis.
CLO1-
4:kDescribekhowkthekdistancekofkthekobservedkstatistickfromkthekparameterkvaluekspecifiedkbykthekn
ullkhypothesis,ksampleksize,kandkone-kvs.ktwo-
sidedktestskaffectkthekstrengthkofkevidencekagainstktheknullkhypothesis.
CLO1-5:kDescribekhowktokcarrykoutkaktheory-based,kone-proportionkz-test.
Section 1.1: Introduction to Chance Models
k k k k k
LO1.1-1:kRecognizekthekdifferencekbetweenkparameterskandkstatistics.
LO1.1-2:kDescribekhowktokusekcoinktossingktoksimulatekoutcomeskfromkakchancekmodelkofkthekran-
kdomkchoicek betweenk twokevents.
LO1.1-3:kUsekthekOnekProportionkappletktokcarrykoutkthekcoinktossingksimulation.
LO1.1-
4:kIdentifykwhetherkorknotkstudykresultskarekstatisticallyksignificantkandkwhetherkorknotkthekchanc
ekmodelkiskakplausiblekexplanationkforkthekdata.
LO1.1-
5:kImplementkthek3Skstrategy:kfindkakstatistic,ksimulatekresultskfromkakchancekmodel,kandkcomme
ntkonkstrengthkofkevidencekagainstkobservedkstudykresultskhappeningkbykchancekalone.
LO1.1-
6:kDifferentiatekbetweenksayingkthekchancekmodelkiskplausiblekandkthekchancekmodelkiskthekcorrectk
explanationkforkthekobservedkdata.
FORkINSTRUCTORkUSEkONLY
, 1-2 TestkBankkforkIntroductionktokStatisticalkInvestigations,k2ndkEdition
Questionsk1kthroughk4:
DokredkuniformkwearersktendktokwinkmorekoftenkthankthosekwearingkbluekuniformskinkTaekwondo
kmatcheskwherekcompetitorskarekrandomlykassignedktokwearkeitherkakredkorkbluekuniform?kInkaksa
mplekofk80kTaekwondokmatches,ktherekwerek45kmatcheskwherekthekredkuniformkwearerkwon.
1. Whatkiskthekparameterkofkinterestkforkthiskstudy?
A. Theklong-runkproportionkofkTaekwondokmatcheskinkwhichkthekredkuniformkwearerkwins
B. Thekproportionkofkmatcheskinkwhichkthekredkuniformkwearerkwinskinkaksamplekofk80kTaekw
ondok matches
C. Whetherkthekredkuniformkwearerkwinskakmatch
D.k 0.50
Ans:kA;kLO:k1.1-1;kDifficulty:kEasy;kType:kMC
2. Whatkiskthekstatistickforkthiskstudy?
A. Theklong-runkproportionkofkTaekwondokmatcheskinkwhichkthekredkuniformkwearerkwins
B. Thekproportionkofkmatcheskinkwhichkthekredkuniformkwearerkwinskinkaksamplekofk80kTaekw
ondok matches
C. Whetherkthekredkuniformkwearerkwinskakmatch
D.k 0.50
Ans:kB;kLO:k1.1-1;kDifficulty:kEasy;kType:kMC
3. Givenkbelowkisktheksimulatedkdistributionkofktheknumberkofk―redkwins‖kthatkcouldkhappenkbykchanc
ekalonekinkaksamplekofk80kmatches.kBasedkonkthisksimulation,kiskourkobservedkresultkstatisticallyksig
nificant?
A. Yes,ksincek45kisklargerkthank40.
B. Yes,ksincekthekheightkofkthekdotplotkabovek45kisksmallerkthankthekheightkofkthekdotplo
tkabovek40.
C. No,ksincek45kiskakfairlyktypicalkoutcomekifkthekcolorkofkthekwinner‘skuniformkwaskdeter
minedkbykchancekalone.
FORkINSTRUCTORkUSEkONLY