CENGAGENOW FOR ANDERSON/SWEENEY/WILLIAM13th EditionCochran Publisher: IACCENGAGEISBN: 9781337094399
CENGAGENOW FOR ANDERSON/SWEENEY/WILLIAM
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Chapter 1 - Data And StatisticsChapter 2 - Descriptive Statistics: Tabular And Graphical DisplaysChapter 2.1 - Summarizing Data For A Categorical VariableChapter 2.2 - Summarizing Data For A Quantitative VariableChapter 2.3 - Summarizing Data For Two Variables Using TablesChapter 2.4 - Summarizing Data For Two Variables Using Graphical DisplaysChapter 3 - Descriptive Statistics: Numerical MeasuresChapter 3.1 - Measures Of LocationChapter 3.2 - Measures Of VariabilityChapter 3.3 - Measures Of Distribution Shape, Relative Location, And Detecting Outliers
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 XChapter 7.6 - Sampling Distribution Of PChapter 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 9.6 - Hypothesis Testing And Decision MakingChapter 9.7 - Calculating The Probability Of Type Ii ErrorsChapter 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 Prediction 631Chapter 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
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Sample Solutions for this Textbook
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Chapter 1, Problem 1SEChapter 2.1, Problem 9EChapter 2.2, Problem 21EChapter 2, Problem 44SEChapter 2, Problem 3CPChapter 3.3, Problem 37EChapter 3, Problem 62SEChapter 3, Problem 3CPChapter 4, Problem 46SE
Chapter 4, Problem 60SEChapter 5.3, Problem 18EChapter 5.5, Problem 33EChapter 5, Problem 59SEChapter 5, Problem 62SEChapter 6.2, Problem 12EChapter 6, Problem 39SEChapter 6, Problem 49SEChapter 7.5, Problem 26EChapter 7.6, Problem 34EChapter 7, Problem 42SEChapter 7, Problem 47SEChapter 8.2, Problem 11EChapter 8.4, Problem 37EChapter 8, Problem 44SEChapter 8, Problem 56SEChapter 8, Problem 2CPChapter 9.3, Problem 12EChapter 9.5, Problem 36EChapter 9, Problem 60SEChapter 9, Problem 2CPChapter 10.2, Problem 9EChapter 10.4, Problem 36EChapter 10, Problem 38SEChapter 10, Problem 1CPChapter 11.1, Problem 2EChapter 11, Problem 23SEChapter 11, Problem 30SEChapter 12.2, Problem 16EChapter 12, Problem 27SEChapter 13.2, Problem 1EChapter 13, Problem 34SEChapter 13, Problem 2CPChapter 14.2, Problem 1EChapter 14, Problem 55SEChapter 14, Problem 1CPChapter 15.2, Problem 9EChapter 15, Problem 49SEChapter 15, Problem 56SEChapter 16, Problem 29SEChapter 17.3, Problem 9EChapter 17, Problem 41SEChapter 17, Problem 1CPChapter 18, Problem 38SEChapter 18, Problem 39SEChapter 19, Problem 16SEChapter 20, Problem 17ECalculation: The data shows that the price per share for Year 1, Year 2, and Year 3. The price...Chapter 21, Problem 18SEChapter 22, Problem 18SE
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