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Statistical Techniques in Business and Economics

Statistical Techniques in Business and Economics 18th Edition

By: Douglas A. Lind
ISBN-10: 1260239470
/ ISBN-13: 9781260788785
Edition: 18th Edition
Language: English
				
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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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