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            Statistics for Business & Economics, Re...
            12th Edition
            David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
            Publisher: South-Western College Pub
            ISBN: 9781285846323

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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 - 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 X BarChapter 7.6 - Sampling Distribution Of P BarChapter 8 - Interval EstimationChapter 8.1 - Population Mean: S KnownChapter 8.2 - Population Mean: S UnknownChapter 8.3 - Determining The Sample SizeChapter 8.4 - Population ProportionChapter 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 Test About A Population MeanChapter 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, Test Of Independence And Goodness Of FitChapter 12.1 - Testing The 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: Validating 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 15.8 - Residual AnalysisChapter 15.9 - Logistic RegressionChapter 16 - Regression Analysis: Model BuildingChapter 16.1 - General Linear ModelChapter 16.2 - Determining When To Add Or Delete VariablesChapter 16.4 - Variable Selection ProceduresChapter 16.5 - Multiple Regression Approach To Experimental DesignChapter 16.6 - Autocorrelation And The Durbin-watson TestChapter 17 - Time Series Analysis And ForecastingChapter 17.2 - Forecast AccuracyChapter 17.3 - Moving Averages And Exponential SmoothingChapter 17.4 - Trend ProjectionChapter 17.5 - Seasonality And TrendChapter 17.6 - Time Series DecompositionChapter 18 - Nonparametric MethodsChapter 18.1 - Sign TestChapter 18.2 - Wilcoxon Signed-rank TestChapter 18.3 - Mann-whitney-wilcoxon TestChapter 18.4 - Kruskal-wallis TestChapter 18.5 - Rank CorrelationChapter 19 - Statistical Methods For Quality ControlChapter 19.2 - Statistical Process ControlChapter 19.3 - Acceptance SamplingChapter 20 - Index NumbersChapter 20.2 - Aggregate Price IndexesChapter 20.3 - Computing An Aggregate Price Index From Price RelativesChapter 20.5 - Deflating A Series By Price IndexesChapter 20.7 - Quantity IndexesChapter 21 - Decision Analysis (on Website)Chapter 21.2 - Decision Making With ProbabilitiesChapter 21.3 - Decision Analysis With Sample InformationChapter 21.4 - Computing Branch Probabilities Using Bayes’ TheoremChapter 22 - Sample Survey (on Website)Chapter 22.4 - Simple Random SamplingChapter 22.5 - Stratified Simple Random SamplingChapter 22.6 - Cluster Sampling

            Book Details

            STATISTICS FOR BUSINESS AND ECONOMICS Revised 12e brings together more than twenty-five years of author experience, sound statistical methodology, a proven problem-scenario approach, and meaningful applications to demonstrate how statistical information informs decisions in the business world. Discover how the most trusted approach to statistics today is Simply Powerful with the latest market-leading text from respected authors Anderson/Sweeney/Williams/Camm/Cochran. STATISTICS FOR BUSINESS AND ECONOMICS Revised 12e introduces sound statistical methodology within a strong applications setting. The authors clearly demonstrate how statistical results provide insights into business decisions and present solutions to contemporary business problems. New cases and more than 350 real business examples and memorable exercises, 150 of which are new in this edition, present the latest statistical data and business information. With this book's comprehensive coverage and unwavering accuracy, you select the topics best for your course, including thorough coverage of the latest versions of MiniTab 16 and Excel 2013, along with StatTools and other leading Excel 2013 statistical add-ins within chapter appendices. Author-written support materials and CengageNOW online course management system provides time-saving, complete support to ensure student understanding.

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            Statistics for Business & Economics, Revised (MindTap Course List)
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