Essentials Of Statistics For Business & Economics - 9th Edition - by David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran - ISBN 9780357045435
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Essentials Of Statistics For Business &...
9th Edition
David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: South-Western College Pub
ISBN: 9780357045435

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Chapter 3.4 - Five-number Summaries And Box PlotsChapter 3.5 - Measures Of Association Between Two VariablesChapter 4 - Introduction To ProbabilityChapter 4.1 - Random Experiments, Counting Rules, And Assigning ProbabilitiesChapter 4.2 - Events And Their ProbabilitiesChapter 4.3 - Some Basic Relationships Of ProbabilityChapter 4.4 - Conditional ProbabilityChapter 4.5 - Bayes’ TheoremChapter 5 - Discrete Probability DistributionsChapter 5.1 - Random VariablesChapter 5.2 - Developing Discrete Probability DistributionsChapter 5.3 - Expected Value And VarianceChapter 5.4 - Bivariate Distributions, Covariance, And Financial PortfoliosChapter 5.5 - Binomial Probability DistributionChapter 5.6 - Poisson Probability DistributionChapter 5.7 - Hypergeometric Probability DistributionChapter 6 - Continuous Probability DistributionsChapter 6.1 - Uniform Probability DistributionChapter 6.2 - Normal Probability DistributionChapter 6.3 - Normal Approximation Of Binomial ProbabilitiesChapter 6.4 - Exponential Probability DistributionChapter 7 - Sampling And Sampling DistributionsChapter 7.2 - Selecting A SampleChapter 7.3 - Point EstimationChapter 7.5 - Sampling Distribution Of XbarChapter 7.6 - Sampling Distribution Of PbarChapter 7.9 - Big Data And Standard Errors Of Sampling DistributionsChapter 8 - Interval EstimationChapter 8.1 - Population Mean: S KnownChapter 8.2 - Population Mean: S KnownChapter 8.3 - Determining The Sample SizeChapter 8.4 - Population ProportionChapter 8.5 - Big Data And Confidence IntervalsChapter 9 - Hypothesis TestsChapter 9.1 - Developing Null And Alternative HypothesesChapter 9.2 - Type I And Type Ii ErrorsChapter 9.3 - Population Mean: S KnownChapter 9.4 - Population Mean: S UnknownChapter 9.5 - Population ProportionChapter 9.7 - Calculating The Probability Of Type Ii ErrorsChapter 9.8 - Determining The Sample Size For A Hypothesis TestChapter 9.9 - Big Data And Hypothesis TestingChapter 10 - Inference About Means And Proportions With Two PopulationsChapter 10.1 - Inferences About The Difference Between Two Population Means:s1 And S2 KnownChapter 10.2 - Inferences About The Difference Between Two Population Means:s1 And S2 UnknownChapter 10.3 - Inferences About The Difference Between Two Population Means: Matched SamplesChapter 10.4 - Inferences About The Difference Between Two Population ProportionsChapter 11 - Inferences About Population VariancesChapter 11.1 - Inferences About A Population VarianceChapter 11.2 - Inferences About Two Population VariancesChapter 12 - Comparing Multiple Proportions, Tests Of Independence And Goodness Of FitChapter 12.1 - Testing For Equality Of Population Proportions For Three Or More PopulationsChapter 12.2 - Test Of IndependenceChapter 12.3 - Goodness Of Fit TestChapter 13 - Experimental Design And Analysis Of VarianceChapter 13.2 - Analysis Of Variance And The Completely Randomized DesignChapter 13.3 - Multiple Comparison ProceduresChapter 13.4 - Randomized Block DesignChapter 13.5 - Factorial ExperimentChapter 14 - Simple Linear RegressionChapter 14.2 - Least Squares MethodChapter 14.3 - Coefficient Of DeterminationChapter 14.5 - Testing For SignificanceChapter 14.6 - Using The Estimated Regression Equation For Estimation And PredictionChapter 14.7 - Computer SolutionChapter 14.8 - Residual Analysis: Model AssumptionsChapter 14.9 - Residual Analysis: Outliers And Influential ObservationsChapter 15 - Multiple RegressionChapter 15.2 - Least Squares MethodChapter 15.3 - Multiple Coefficient Of DeterminationChapter 15.5 - Testing For SignificanceChapter 15.6 - Using The Estimated Regression Equation For Estimation And PredictionChapter 15.7 - Categorical Independent VariablesChapter 15.9 - Logistic Regression

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