Statistical Techniques in Business and Economics
Lýsing:
Statistical Techniques in Business and Economics, 18e is a best seller, originally published in 1967 to provide students majoring in management, marketing, finance, accounting, economics, and other fields of business administration with an introductory survey of descriptive and inferential statistics. Its hallmark presentation boasts a step by step approach that was written so clearly that any student can learn and succeed in Business Statistics.
Its simple language and use of multiple examples focus on business applications, but also relate to the current world of the college student. This step-by-step approach enhances performance, accelerates preparedness, and significantly improves motivation. Lind's real-world examples, comprehensive coverage, and superior pedagogy that now includes data analytics coverage, combined with a complete digital solution help students achieve higher outcomes in the course.
Annað
- Höfundar: Douglas Lind, William Marchal, Samuel Wathen
- Útgáfa:18
- Útgáfudagur: 2020-05-01
- Hægt að prenta út 2 bls.
- Hægt að afrita 2 bls.
- Format:ePub
- ISBN 13: 9781260579611
- Print ISBN: 9781260570489
- ISBN 10: 1260579611
Efnisyfirlit
- Cover
- Halftitle
- The McGraw-Hill/Irwin Series in Operations and Decision Science
- Title
- Copyright
- Dedication
- A Note from the Authors
- How are Chapters Organized to Engage Students and Promote Learning?
- How Does this Text Reinforce Student Learning?
- Connect
- Additional Resources
- Acknowledgments
- Enhancements to Statistical Techniques in Business & Economics, 18e
- Brief Contents
- Contents
- 1 What Is Statistics?
- Introduction
- Why Study Statistics?
- What Is Meant by Statistics?
- Types of Statistics
- Descriptive Statistics
- Inferential Statistics
- Types of Variables
- Levels of Measurement
- Nominal-Level Data
- Ordinal-Level Data
- Interval-Level Data
- Ratio-Level Data
- EXERCISES
- Ethics and Statistics
- Basic Business Analytics
- Chapter Summary
- Chapter Exercises
- Data Analytics
- 2 Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation
- Introduction
- Constructing Frequency Tables
- Relative Class Frequencies
- Graphic Presentation of Qualitative Data
- EXERCISES
- Constructing Frequency Distributions
- Relative Frequency Distribution
- EXERCISES
- Graphic Presentation of a Distribution
- Histogram
- Frequency Polygon
- EXERCISES
- Cumulative Distributions
- EXERCISES
- Chapter Summary
- Chapter Exercises
- Data Analytics
- 3 Describing Data: Numerical Measures
- Introduction
- Measures of Location
- The Population Mean
- The Sample Mean
- Properties of the Arithmetic Mean
- EXERCISES
- The Median
- The Mode
- Software Solution
- EXERCISES
- The Relative Positions of the Mean, Median, and Mode
- EXERCISES
- The Weighted Mean
- EXERCISES
- The Geometric Mean
- EXERCISES
- Why Study Dispersion?
- Range
- Variance
- EXERCISES
- Population Variance
- Population Standard Deviation
- EXERCISES
- Sample Variance and Standard Deviation
- Software Solution
- EXERCISES
- Interpretation and Uses of the Standard Deviation
- Chebyshev’s Theorem
- The Empirical Rule
- EXERCISES
- The Mean and Standard Deviation of Grouped Data
- Arithmetic Mean of Grouped Data
- Standard Deviation of Grouped Data
- EXERCISES
- Ethics and Reporting Results
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- 4 Describing Data: Displaying and Exploring Data
- Introduction
- Dot Plots
- EXERCISES
- Measures of Position
- Quartiles, Deciles, and Percentiles
- EXERCISES
- Box Plots
- EXERCISES
- Skewness
- EXERCISES
- Describing the Relationship between Two Variables
- Correlation Coefficient
- Contingency Tables
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- A REVIEW OF CHAPTERS 1–4
- PROBLEMS
- CASES
- PRACTICE TEST
- 5 A Survey of Probability Concepts
- Introduction
- What Is a Probability?
- Approaches to Assigning Probabilities
- Classical Probability
- Empirical Probability
- Subjective Probability
- EXERCISES
- Rules of Addition for Computing Probabilities
- Special Rule of Addition
- Complement Rule
- The General Rule of Addition
- EXERCISES
- Rules of Multiplication to Calculate Probability
- Special Rule of Multiplication
- General Rule of Multiplication
- Contingency Tables
- Tree Diagrams
- EXERCISES
- Bayes’ Theorem
- EXERCISES
- Principles of Counting
- The Multiplication Formula
- The Permutation Formula
- The Combination Formula
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- 6 Discrete Probability Distributions
- Introduction
- What Is a Probability Distribution?
- Random Variables
- Discrete Random Variable
- Continuous Random Variable
- The Mean, Variance, and Standard Deviation of a Discrete Probability Distribution
- Mean
- Variance and Standard Deviation
- EXERCISES
- Binomial Probability Distribution
- How Is a Binomial Probability Computed?
- Binomial Probability Tables
- EXERCISES
- Cumulative Binomial Probability Distributions
- EXERCISES
- Hypergeometric Probability Distribution
- EXERCISES
- Poisson Probability Distribution
- EXERCISES
- Chapter Summary
- Chapter Exercises
- Data Analytics
- 7 Continuous Probability Distributions
- Introduction
- The Family of Uniform Probability Distributions
- EXERCISES
- The Family of Normal Probability Distributions
- The Standard Normal Probability Distribution
- Applications of the Standard Normal Distribution
- The Empirical Rule
- EXERCISES
- Finding Areas under the Normal Curve
- EXERCISES
- EXERCISES
- EXERCISES
- The Family of Exponential Distributions
- EXERCISES
- Chapter Summary
- Chapter Exercises
- Data Analytics
- A REVIEW OF CHAPTERS 5–7
- PROBLEMS
- CASES
- PRACTICE TEST
- 8 Sampling, Sampling Methods, and the Central Limit Theorem
- Introduction
- Research and Sampling
- Sampling Methods
- Simple Random Sampling
- Systematic Random Sampling
- Stratified Random Sampling
- Cluster Sampling
- EXERCISES
- Sample Mean as a Random Variable
- Sampling Distribution of the Sample Mean
- EXERCISES
- The Central Limit Theorem
- Standard Error of The Mean
- EXERCISES
- Using the Sampling Distribution of the Sample Mean
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- 9 Estimation and Confidence Intervals
- Introduction
- Point Estimate for a Population Mean
- Confidence Intervals for a Population Mean
- Population Standard Deviation, Known σ
- A Computer Simulation
- EXERCISES
- Population Standard Deviation, σ Unknown
- EXERCISES
- A Confidence Interval for a Population Proportion
- EXERCISES
- Choosing an Appropriate Sample Size
- Sample Size to Estimate a Population Mean
- Sample Size to Estimate a Population Proportion
- EXERCISES
- Finite-Population Correction Factor
- EXERCISES
- Chapter Summary
- Chapter Exercises
- Data Analytics
- A REVIEW OF CHAPTERS 8–9
- PROBLEMS
- CASES
- PRACTICE TEST
- 10 One-Sample Tests of Hypothesis
- Introduction
- What Is Hypothesis Testing?
- Six-Step Procedure for Testing a Hypothesis
- Step 1: State the Null Hypothesis (H0) and the Alternate Hypothesis (H1)
- Step 2: Select a Level of Significance
- Step 3: Select the Test Statistic
- Step 4: Formulate the Decision Rule
- Step 5: Make a Decision
- Step 6: Interpret the Result
- One-Tailed and Two-Tailed Hypothesis Tests
- Hypothesis Testing for a Population Mean: Known Population Standard Deviation
- A Two-Tailed Test
- A One-Tailed Test
- p-Value in Hypothesis Testing
- EXERCISES
- Hypothesis Testing for a Population Mean: Population Standard Deviation Unknown
- EXERCISES
- A Statistical Software Solution
- EXERCISES
- Type II Error
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- 11 Two-Sample Tests of Hypothesis
- Introduction
- Two-Sample Tests of Hypothesis: Independent Samples
- EXERCISES
- Comparing Population Means with Unknown Population Standard Deviations
- Two-Sample Pooled Test
- EXERCISES
- Unequal Population Standard Deviations
- EXERCISES
- Two-Sample Tests of Hypothesis: Dependent Samples
- Comparing Dependent and Independent Samples
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- 12 Analysis of Variance
- Introduction
- Comparing Two Population Variances
- The F-Distribution
- Testing a Hypothesis of Equal Population Variances
- EXERCISES
- ANOVA: Analysis of Variance
- ANOVA Assumptions
- The ANOVA Test
- EXERCISES
- Inferences about Pairs of Treatment Means
- EXERCISES
- Two-Way Analysis of Variance
- EXERCISES
- Two-Way ANOVA with Interaction
- Interaction Plots
- Testing for Interaction
- Hypothesis Tests for Interaction
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- A REVIEW OF CHAPTERS 10–12
- PROBLEMS
- CASES
- PRACTICE TEST
- 13 Correlation and Linear Regression
- Introduction
- What Is Correlation Analysis?
- The Correlation Coefficient
- EXERCISES
- Testing the Significance of the Correlation Coefficient
- EXERCISES
- Regression Analysis
- Least Squares Principle
- Drawing the Regression Line
- EXERCISES
- Testing the Significance of the Slope
- EXERCISES
- Evaluating a Regression Equation’s Ability to Predict
- The Standard Error of Estimate
- The Coefficient of Determination
- EXERCISES
- Relationships among the Correlation Coefficient, the Coefficient of Determination, and the Standard Error of Estimate
- EXERCISES
- Interval Estimates of Prediction
- Assumptions Underlying Linear Regression
- Constructing Confidence and Prediction Intervals
- EXERCISES
- Transforming Data
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- 14 Multiple Regression Analysis
- Introduction
- Multiple Regression Analysis
- EXERCISES
- Evaluating a Multiple Regression Equation
- The ANOVA Table
- Multiple Standard Error of Estimate
- Coefficient of Multiple Determination
- Adjusted Coefficient of Determination
- EXERCISES
- Inferences in Multiple Linear Regression
- Global Test: Testing the Multiple Regression Model
- Evaluating Individual Regression Coefficients
- EXERCISES
- Evaluating the Assumptions of Multiple Regression
- Linear Relationship
- Variation in Residuals Same for Large and Small ŷ Values
- Distribution of Residuals
- Multicollinearity
- Independent Observations
- Qualitative Independent Variables
- Regression Models with Interaction
- Stepwise Regression
- EXERCISES
- Review of Multiple Regression
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- A REVIEW OF CHAPTERS 13–14
- PROBLEMS
- CASES
- PRACTICE TEST
- 15 Nonparametric Methods: Nominal Level Hypothesis Tests
- Introduction
- Test a Hypothesis of a Population Proportion
- EXERCISES
- Two-Sample Tests about Proportions
- EXERCISES
- Goodness-of-Fit Tests: Comparing Observed and Expected Frequency Distributions
- Hypothesis Test of Equal Expected Frequencies
- EXERCISES
- Hypothesis Test of Unequal Expected Frequencies
- Limitations of Chi-Square
- EXERCISES
- Testing the Hypothesis That a Distribution Is Normal
- EXERCISES
- Contingency Table Analysis
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- 16 Nonparametric Methods: Analysis of Ordinal Data
- Introduction
- The Sign Test
- EXERCISES
- Testing a Hypothesis About a Median
- EXERCISES
- Wilcoxon Signed-Rank Test for Dependent Populations
- EXERCISES
- Wilcoxon Rank-Sum Test for Independent Populations
- EXERCISES
- Kruskal-Wallis Test: Analysis of Variance by Ranks
- EXERCISES
- Rank-Order Correlation
- Testing the Significance of rs
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- Data Analytics
- A REVIEW OF CHAPTERS 15–16
- PROBLEMS
- CASES
- PRACTICE TEST
- 17 Index Numbers
- Introduction
- Simple Index Numbers
- Why Convert Data to Indexes?
- Construction of Index Numbers
- EXERCISES
- Unweighted Indexes
- Simple Average of the Price Indexes
- Simple Aggregate Index
- Weighted Indexes
- Laspeyres Price Index
- Paasche Price Index
- Fisher’s Ideal Index
- EXERCISES
- Value Index
- EXERCISES
- Special-Purpose Indexes
- Consumer Price Index
- Producer Price Index
- Dow Jones Industrial Average (DJIA)
- EXERCISES
- Consumer Price Index
- Special Uses of the Consumer Price Index
- Shifting the Base
- EXERCISES
- Chapter Summary
- Chapter Exercises
- Data Analytics
- 18 Forecasting with Time Series Analysis
- Introduction
- Time Series Patterns
- Trend
- Seasonality
- Cycles
- Irregular Component
- EXERCISES
- Modeling Stationary Time Series: Forecasts Using Simple Moving Averages
- Forecasting Error
- EXERCISES
- Modeling Stationary Time Series: Simple Exponential Smoothing
- EXERCISES
- Modeling Time Series with Trend: Regression Analysis
- Regression Analysis
- EXERCISES
- The Durbin-Watson Statistic
- EXERCISES
- Modeling Time Series with Seasonality: Seasonal Indexing
- EXERCISES
- Chapter Summary
- Chapter Exercises
- Data Analytics
- A REVIEW OF CHAPTERS 17–18
- PROBLEMS
- PRACTICE TEST
- 19 Statistical Process Control and Quality Management
- Introduction
- A Brief History of Quality Control
- Six Sigma
- Sources of Variation
- Diagnostic Charts
- Pareto Charts
- Fishbone Diagrams
- EXERCISES
- Purpose and Types of Quality Control Charts
- Control Charts for Variables
- Range Charts
- In-Control and Out-of-Control Situations
- EXERCISES
- Attribute Control Charts
- p-Charts
- c-Bar Charts
- EXERCISES
- Acceptance Sampling
- EXERCISES
- Chapter Summary
- Pronunciation Key
- Chapter Exercises
- 20 An Introduction to Decision Theory
- Introduction
- Elements of a Decision
- Decision Making Under Conditions of Uncertainty
- Payoff Table
- Expected Payoff
- EXERCISES
- Opportunity Loss
- EXERCISES
- Expected Opportunity Loss
- EXERCISES
- Maximin, Maximax, and Minimax Regret Strategies
- Value of Perfect Information
- Sensitivity Analysis
- EXERCISES
- Decision Trees
- Chapter Summary
- Chapter Exercises
- APPENDIXES
- Appendix A: Data Sets
- Appendix B: Tables
- Appendix C: Answers to Odd-Numbered Chapter Exercises
- Review Exercises
- Solutions to Practice Tests
- Appendix D: Answers to Self-Review
- Glossary
- Index
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- Höfundur : 15158
- Útgáfuár : 2020
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