Statistics (13th Edition) - 13th Edition - by James T. McClave, Terry T Sincich - ISBN 9780134080215
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Statistics (13th Edition)
13th Edition
James T. McClave, Terry T Sincich
Publisher: PEARSON
ISBN: 9780134080215

Solutions for Statistics (13th Edition)

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Chapter 2.9 - Distorting The Truth With Descriptive TechniquesChapter 3 - ProbabilityChapter 3.1 - Events, Sample Spaces, And ProbabilityChapter 3.4 - The Additive Rule And Mutually Exclusive EventsChapter 3.6 - The Multiplicative Rule And Independent EventsChapter 3.7 - Some Additional Counting Rules (optional)Chapter 3.8 - Bayes's RuleChapter 4 - Discrete Random VariablesChapter 4.1 - Two Types Of Random VariablesChapter 4.2 - Probability Distributions For Discrete Random VariablesChapter 4.3 - Expected Values Of Discrete Random VariablesChapter 4.4 - The Binomial DistributionChapter 4.5 - The Poisson Random Variable (optional)Chapter 4.6 - The Hypergeometric Random Variable (optional)Chapter 5 - Continuous Random VariablesChapter 5.2 - The Uniform DistributionChapter 5.3 - The Normal DistributionChapter 5.4 - Descriptive Methods For Assessing NormalityChapter 5.5 - Approximating A Binomial Distribution With A Normal Distribution (optional)Chapter 5.6 - The Exponential Distribution (optional)Chapter 6 - Sampling DistributionsChapter 6.1 - The Concept Of A Sampling DistributionChapter 6.2 - Properties Of Sampling Distributions: Unbiasedness And Minimum VarianceChapter 6.3 - The Sampling Distribution Of The Sample Mean And The Central Limit TheoremChapter 6.4 - The Sampling Distribution Of The Sample ProportionChapter 7 - Inferences Based On A Single Sample: Estimation With Confidence IntervalsChapter 7.2 - Confidence Interval For A Population Mean: Normal (z) StatisticChapter 7.3 - Confidence Interval For A Population Mean: Student's T-statisticChapter 7.4 - Large-sample Confidence Interval For A Population ProportionChapter 7.5 - Determining The Sample SizeChapter 7.6 - Confidence Interval For A Population VarianceChapter 8 - Inferences Based On A Single Sample: Tests Of HypothesesChapter 8.2 - Formulating Hypotheses And Setting Up The Rejection RegionChapter 8.3 - Observed Significance Levels: P-valuesChapter 8.4 - Test Of Hypothesis About A Population Mean: Normal (z) StatisticChapter 8.5 - Test Of Hypothesis About A Population Mean: Student's T-statisticChapter 8.6 - Large-sample Test Of Hypothesis About A Population ProportionChapter 8.7 - Calculating Type Ii Error Probabilities: More About β (optional)Chapter 8.8 - Test Of Hypothesis About A Population Variance (optional)Chapter 9 - Inferences Based On Two Samples: Confidence Intervals And Tests Of HypothesesChapter 9.2 - Comparing Two Population Means: Independent SamplingChapter 9.3 - Comparing Two Population Means: Paired Difference ExperimentsChapter 9.4 - Comparing Two Population Proportions: Independent SamplingChapter 9.5 - Determining The Required Sample SizeChapter 9.6 - Comparing Two Population Variances: Independent SamplingChapter 10 - Analysis Of Variance: Comparing More Than Two MeansChapter 10.1 - Elements Of A Designed ExperimentChapter 10.2 - The Completely Randomized Design: Single FactorChapter 10.3 - Multiple Comparisons Of MeansChapter 10.4 - The Randomized Block DesignChapter 10.5 - Factorial Experiments: Two FactorsChapter 11 - Simple Linear RegressionChapter 11.1 - Probabilistic ModelsChapter 11.2 - Fitting The Model: The Least Squares ApproachChapter 11.3 - Model AssumptionsChapter 11.4 - Assessing The Utility Of The Model: Making Inferences About The SlopeChapter 11.5 - The Coefficients Of Correlation And DeterminationChapter 11.6 - Using The Model For Estimation And PredictionChapter 11.7 - A Complete ExampleChapter 12 - Multiple Regression And Model BuildingChapter 12.3 - Evaluating Overall Model UtilityChapter 12.4 - Using The Model For Estimation And PredictionChapter 12.5 - Interaction ModelsChapter 12.6 - Quadratic And Other Higher-order ModelsChapter 12.7 - Qualitative (dummy) Variable ModelsChapter 12.8 - Models With Both Quantitative And Qualitative VariablesChapter 12.9 - Comparing Nested ModelsChapter 12.10 - Stepwise RegressionChapter 12.12 - Some Pitfalls: Estimability, Multicollinearity, And ExtrapolationChapter 13 - Categorical Data AnalysisChapter 13.2 - Testing Categorical Probabilities: One-way TableChapter 13.3 - Testing Categorical Probabilities: Two-way (contingency)tableChapter 14 - Nonparametric Statistics (available Online)Chapter 14.2 - Single Population InferencesChapter 14.3 - Comparing Two Populations: Independent SamplesChapter 14.4 - Comparing Two Populations: Paired Difference ExperimentChapter 14.5 - Comparing Three Or More Populations: Completely Randomized DesignChapter 14.6 - Comparing Three Or More Populations: Randomized Block DesignChapter 14.7 - Rank Correlation

Book Details

A Contemporary Classic.

Classic, yet contemporary; theoretical, yet applied–McClave & Sincich's Statistics gives you the best of both worlds. This text offers a trusted, comprehensive introduction to statistics that emphasizes inference and integrates real data throughout. The authors stress the development of statistical thinking, the assessment of credibility, and value of the inferences made from data. This new edition is extensively revised with an eye on clearer, more concise language throughout the text and in the exercises.

Ideal for one- or two-semester courses in introductory statistics, this text assumes a mathematical background of basic algebra. Flexibility is built in for instructors who teach a more advanced course, with optional footnotes about calculus and the underlying theory.

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More Editions of This Book

Corresponding editions of this textbook are also available below:

Statistics, 11th Edition (book & Cd)
11th Edition
ISBN: 9780132069519
Statistics- Text Only
10th Edition
ISBN: 9780007028368
Statistics For Business And Economics
2nd Edition
ISBN: 9781269198387
13th Edition
ISBN: 9780135959824
13th Edition
ISBN: 9780135819999

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