Statistics for Business & Economics, Global Edition
6.990 kr.
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For courses in Introductory Business Statistics. Real data. Real decisions. Real business. Statistics for Business and Economics by McClave, Benson,and Sincich introduces statistics in the context of contemporarybusiness. Inference is emphasized, with extensive coverageof data collection and analysis as needed to evaluate the reported results ofstatistical studies and make good decisions. The authorsapply concepts with real data.
Annað
- Höfundar: James T. McClave, P. George Benson, Terry T Sincich
- Útgáfa:14
- Útgáfudagur: 2021-11-08
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- Format:Page Fidelity
- ISBN 13: 9781292413525
- Print ISBN: 9781292413396
- ISBN 10: 1292413522
Efnisyfirlit
- Applet Correlation
- Half Title
- Title Page
- Copyright
- Contents
- Preface
- Acknowledgments
- MyLab Statistics Resources for Success
- Chapter 1. Statistics, Data, and Statistical Thinking
- 1.1 The Science of Statistics
- 1.2 Types of Statistical Applications in Business
- 1.3 Fundamental Elements of Statistics
- 1.4 Processes (Optional)
- 1.5 Types of Data
- 1.6 Collecting Data: Sampling and Related Issues
- 1.7 Business Analytics: Critical Thinking with Statistics
- Statistics In Action: A 20/20 View of Surveys and Studies: Facts or Fake News?
- Activity 1.1: Keep the Change: Collecting Data
- Activity 1.2: Identifying Misleading Statistics
- Using Technology: Accessing and Listing Data
- Chapter 2. Methods for Describing Sets of Data
- 2.1 Describing Qualitative Data
- 2.2 Graphical Methods for Describing Quantitative Data
- 2.3 Numerical Measures of Central Tendency
- 2.4 Numerical Measures of Variability
- 2.5 Using the Mean and Standard Deviation to Describe Data
- 2.6 Numerical Measures of Relative Standing
- 2.7 Methods for Detecting Outliers: Box Plots and z-Scores
- 2.8 Graphing Bivariate Relationships (Optional)
- 2.9 The Time Series Plot (Optional)
- 2.10 Distorting the Truth with Descriptive Techniques
- Statistics In Action: Can Money Buy Love?
- Activity 2.1: Real Estate Sales
- Activity 2.2: Keep the Change: Measures of Central Tendency and Variability
- Using Technology: Describing Data
- Making Business Decisions: The Kentucky Milk Case—Part I (Covers Chapters 1 and 2)
- Chapter 3. Probability
- 3.1 Events, Sample Spaces, and Probability
- 3.2 Unions and Intersections
- 3.3 Complementary Events
- 3.4 The Additive Rule and Mutually Exclusive Events
- 3.5 Conditional Probability
- 3.6 The Multiplicative Rule and Independent Events
- 3.7 Bayes’s Rule
- Statistics In Action: Lotto Buster!
- Activity 3.1: Exit Polls: Conditional Probability
- Activity 3.2: Keep the Change: Independent Events
- Using Technology: Combinations and Permutations
- Chapter 4. Random Variables and Probability Distributions
- 4.1 Two Types of Random Variables
- Part I: Discrete Random Variables
- 4.2 Probability Distributions for Discrete Random Variables
- 4.3 The Binomial Distribution
- 4.4 Other Discrete Distributions: Poisson and Hypergeometric
- Part II: Continuous Random Variables
- 4.5 Probability Distributions for Continuous Random Variables
- 4.6 The Normal Distribution
- 4.7 Descriptive Methods for Assessing Normality
- 4.8 Other Continuous Distributions: Uniform and Exponential
- Statistics In Action: Probability in a Reverse Cocaine Sting: Was Cocaine Really Sold?
- Activity 4.1: Warehouse Club Memberships: Exploring a Binomial Random Variable
- Activity 4.2: Identifying the Type of Probability Distribution
- Using Technology: Discrete Probabilities, Continuous Probabilities, and Normal Probability Plots
- Chapter 5. Sampling Distributions
- 5.1 The Concept of a Sampling Distribution
- 5.2 Properties of Sampling Distributions: Unbiasedness and Minimum Variance
- 5.3 The Sampling Distribution of the Sample Mean and the Central Limit Theorem
- 5.4 The Sampling Distribution of the Sample Proportion
- Statistics In Action: The Insomnia Pill: Is It Effective?
- Activity 5.1: Simulating a Sampling Distribution—Cell Phone Usage
- Using Technology: Simulating a Sampling Distribution
- Making Business Decisions: The Furniture Fire Case (Covers Chapters 3–5)
- Chapter 6. Inferences Based on a Single Sample: Estimation with Confidence Intervals
- 6.1 Identifying and Estimating the Target Parameter
- 6.2 Confidence Interval for a Population Mean: Normal (z) Statistic
- 6.3 Confidence Interval for a Population Mean: Student’s t-Statistic
- 6.4 Large-Sample Confidence Interval for a Population Proportion
- 6.5 Determining the Sample Size
- 6.6 Finite Population Correction for Simple Random Sampling (Optional)
- 6.7 Confidence Interval for a Population Variance (Optional)
- Statistics In Action: Medicare Fraud Investigations
- Activity 6.1: Conducting a Pilot Study
- Using Technology: Confidence Intervals and Sample Size Determination
- Chapter 7. Inferences Based on a Single Sample: Tests of Hypotheses
- 7.1 The Elements of a Test of Hypothesis
- 7.2 Formulating Hypotheses and Setting Up the Rejection Region
- 7.3 Observed Significance Levels: p-Values
- 7.4 Test of Hypothesis About a Population Mean: Normal (z) Statistic
- 7.5 Test of Hypothesis About a Population Mean: Student’s t-Statistic
- 7.6 Large-Sample Test of Hypothesis About a Population Proportion
- 7.7 Test of Hypothesis About a Population Variance
- 7.8 Calculating Type II Error Probabilities: More About β (Optional)
- Statistics In Action: Diary of a Kleenex® User—How Many Tissues in a Box?
- Activity 7.1: Challenging a Company’s Claim: Tests of Hypotheses
- Activity 7.2: Keep the Change: Tests of Hypotheses
- Using Technology: Tests of Hypotheses
- Chapter 8. Inferences Based on Two Samples: Confidence Intervals and Tests of Hypotheses
- 8.1 Identifying the Target Parameter
- 8.2 Comparing Two Population Means: Independent Sampling
- 8.3 Comparing Two Population Means: Paired Difference Experiments
- 8.4 Comparing Two Population Proportions: Independent Sampling
- 8.5 Determining the Required Sample Size
- 8.6 Comparing Two Population Variances: Independent Sampling
- Statistics In Action: ZixIt Corp. v. Visa USA Inc.—A Libel Case
- Activity 8.1: Box Office Receipts: Comparing Population Means
- Activity 8.2: Keep the Change: Inferences Based on Two Samples
- Using Technology: Two-Sample Inferences
- Making Business Decisions: The Kentucky Milk Case—Part II (Covers Chapters 6–8)
- Chapter 9. Design of Experiments and Analysis of Variance
- 9.1 Elements of a Designed Experiment
- 9.2 The Completely Randomized Design: Single Factor
- 9.3 Multiple Comparisons of Means
- 9.4 The Randomized Block Design
- 9.5 Factorial Experiments: Two Factors
- Statistics In Action: Tax Compliance Behavior—Factors That Affect Your Level of Risk Taking When F
- Activity 9.1: Designed vs. Observational Experiments
- Using Technology: Analysis of Variance
- Chapter 10. Categorical Data Analysis
- 10.1 Categorical Data and the Multinomial Experiment
- 10.2 Testing Category Probabilities: One-Way Table
- 10.3 Testing Category Probabilities: Two-Way (Contingency) Table
- 10.4 A Word of Caution About Chi-Square Tests
- Statistics In Action: The Illegal Transplant Tissue Trade—Who Is Responsible for Paying Damages?
- Activity 10.1: Binomial vs. Multinomial Experiments
- Activity 10.2: Contingency Tables
- Using Technology: Chi-Square Analyses
- Making Business Decisions: Discrimination in the Workplace (Covers Chapters 9–10)
- Chapter 11. Simple Linear Regression
- 11.1 Probabilistic Models
- 11.2 Fitting the Model: The Least Squares Approach
- 11.3 Model Assumptions
- 11.4 Assessing the Utility of the Model: Making Inferences About the Slope β1
- 11.5 The Coefficients of Correlation and Determination
- 11.6 Using the Model for Estimation and Prediction
- 11.7 A Complete Example
- Statistics In Action: Legal Advertising—Does It Pay?
- Activity 11.1: Applying Simple Linear Regression to Your Favorite Data
- Using Technology: Simple Linear Regression
- Chapter 12. Multiple Regression and Model Building
- 12.1 Multiple Regression Models
- Part I: First-Order Models With Quantitative Independent variables
- 12.2 Estimating and Making Inferences About the β Parameters
- 12.3 Evaluating Overall Model Utility
- 12.4 Using the Model for Estimation and Prediction
- Part II: Model Building In Multiple Regression
- 12.5 Interaction Models
- 12.6 Quadratic and Other Higher-Order Models
- 12.7 Qualitative (Dummy) Variable Models
- 12.8 Models with Both Quantitative and Qualitative Variables
- 12.9 Comparing Nested Models
- 12.10 Stepwise Regression
- Part III: Multiple Regression Diagnostics
- 12.11 Residual Analysis: Checking the Regression Assumptions
- 12.12 Some Pitfalls: Estimability, Multicollinearity, and Extrapolation
- Statistics In Action: Bid Rigging in the Highway Construction Industry
- Activity 12.1: Insurance Premiums: Collecting Data for Several Variables
- Activity 12.2: Collecting Data and Fitting a Multiple Regression Model
- Using Technology: Multiple Regression
- Making Business Decisions: The Condo Sales Case (Covers Chapters 11–12)
- Chapter 13. Methods for Quality Improvement: Statistical Process Control
- 13.1 Quality, Processes, and Systems
- 13.2 Statistical Control
- 13.3 The Logic of Control Charts
- 13.4 A Control Chart for Monitoring the Mean of a Process: The x-Chart
- 13.5 A Control Chart for Monitoring the Variation of a Process: The R-Chart
- 13.6 A Control Chart for Monitoring the Proportion of Defectives Generated by a Process: The p-Chart
- 13.7 Diagnosing the Causes of Variation
- 13.8 Capability Analysis
- Statistics In Action: Testing Jet Fuel Additive for Safety
- Activity 13.1: Quality Control: Consistency
- Using Technology: Control Charts
- Making Business Decisions: The Gasket Manufacturing Case (Covers Chapter 13)
- Chapter 14. Time Series: Descriptive Analyses, Models, and Forecasting
- 14.1 Descriptive Analysis: Index Numbers
- 14.2 Descriptive Analysis: Exponential Smoothing
- 14.3 Time Series Components
- 14.4 Forecasting: Exponential Smoothing
- 14.5 Forecasting Trends: Holt’s Method
- 14.6 Measuring Forecast Accuracy: MAD and RMSE
- 14.7 Forecasting Trends: Simple Linear Regression
- 14.8 Seasonal Regression Models
- 14.9 Autocorrelation and the Durbin-Watson Test
- Statistics In Action: Forecasting the Monthly Sales of a New Cold Medicine
- Activity 14.1: Time Series
- Using Technology: Forecasting
- Chapter 15. Nonparametric Statistics
- 15.1 Introduction: Distribution-Free Tests
- 15.2 Single Population Inferences
- 15.3 Comparing Two Populations: Independent Samples
- 15.4 Comparing Two Populations: Paired Difference Experiment
- 15.5 Comparing Three or More Populations: Completely Randomized Design
- 15.6 Comparing Three or More Populations: Randomized Block Design
- 15.7 Rank Correlation
- Statistics In Action: Pollutants at a Housing Development—A Case of Mishandling Small Samples
- Activity 15.1: Keep the Change: Nonparametric Statistics
- Using Technology: Nonparametric Tests
- Making Business Decisions: Detecting "Sales Chasing" (Covers Chapters 10 and 15)
- Appendix A: Summation Notation
- Appendix B: Basic Counting Rules
- Appendix C: Calculation Formulas for Analysis of Variance
- C.1 Formulas for the Calculations in the Completely Randomized Design
- C.2 Formulas for the Calculations in the Randomized Block Design
- C.3 Formulas for the Calculations for a Two-Factor Factorial Experiment
- C.4 Tukey’s Multiple Comparisons Procedure (Equal Sample Sizes)
- C.5 Bonferroni Multiple Comparisons Procedure (Pairwise Comparisons)
- C.6 Scheffé’s Multiple Comparisons Procedure (Pairwise Comparisons)
- Appendix D: Tables
- Table I Binomial Probabilities
- Table II Normal Curve Areas
- Table III Critical Values of t
- Table IV Critical Values of x2
- Table V Percentage Points of the F-Distribution, α = .10
- Table VI Percentage Points of the F-Distribution, α = .05
- Table VII Percentage Points of the F-Distribution, α = .025
- Table VIII Percentage Points of the F-Distribution, α = .01
- Table IX Control Chart Constants
- Table X Critical Values for the Durbin-Watson d-Statistic, α = .05
- Table XI Critical Values for the Durbin-Watson d-Statistic, α = .01
- Table XII Critical Values of TL and TU for the Wilcoxon Rank Sum Test: Independent Samples
- Table XIII Critical Values of T0 in the Wilcoxon Paired Difference Signed Rank Test
- Table XIV Critical Values of Spearman’s Rank Correlation Coefficient
- Table XV Critical Values of the Studentized Range, α = .05
- Answers to Selected Exercises
- Index
- Credits
- Selected Formulas
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- Gerð : 208
- Höfundur : 9648
- Útgáfuár : 2021
- Leyfi : 380