Business Statistics: A First Course, Global Edition

Höfundar: David M. Levine; Kathryn A. Szabat; David F. Stephan (Útgáfa: 8)
Business Statistics: A First Course, Global Edition

Kaup valmöguleikar

Tölfræði er nauðsynleg öllum nemendum í viðskiptafræði. Business Statistics: A First Course sýnir nemendum hvaða hlutverki tölfræði gegnir í starfsframa þeirra með dæmum úr öllum helstu starfssviðum fyrirtækja. Í 8. alþjóðlegu útgáfunni er áfram unnið að nýjungum og umbótum í kennslu námsefnisins, með hliðsjón af viðmiðum helstu samtaka á sviði tölfræði og viðskiptafræða, ASA og DSI, auk fjölbreyttrar reynslu höfunda.

Með nýjum dæmum, tilvikslýsingum og verkefnum er áfram lögð áhersla á túlkun niðurstaðna, mat á forsendum og umfjöllun um næstu skref í gagnadrifinni ákvarðanatöku. Höfundarnir telja að þessi nálgun nýtist nemendum betur í framtíðarstörfum en áhersla á handvirka útreikninga. Bókin er hnitmiðuð og sniðin að þörfum námskeiðs sem kennt er á einni önn. Hún tilheyrir hinni rótgrónu Berenson/Levine-bókaröð.

Nánar um bókina

Útgefandi
Pearson International Content
ISBN
9781292320489
Print ISBN
9781292320366
Format
Page Fidelity (PDF)
Útgáfa
8
Höfundar
David M. Levine; Kathryn A. Szabat; David F. Stephan
Tungumál
English
Útgefið
2019-10-17
Prent takmörkun á líftíma
100

Kaflar

  • Title Page
  • Copyright Page
  • About the Authors
  • Brief Contents
  • Contents
  • Preface
  • First Things First
  • USING STATISTICS: “The Price of Admission”
  • FTF.1 Think Differently About Statistics
  • Statistics: A Way of Thinking
  • Statistics: An Important Part of Your Business Education
  • FTF.2 Business Analytics: The Changing Face of Statistics
  • “Big Data”
  • FTF.3 Starting Point for Learning Statistics
  • Statistic
  • Can Statistics (pl., statistic) Lie?
  • FTF.4 Starting Point for Using Software
  • Using Software Properly
  • REFERENCES
  • KEY TERMS
  • EXCEL GUIDE
  • EG.1 Getting Started with Excel
  • EG.2 Entering Data
  • EG.3 Open or Save a Workbook
  • EG.4 Working with a Workbook
  • EG.5 Print a Worksheet
  • EG.6 Reviewing Worksheets
  • EG.7 If You use the Workbook Instructions
  • JMP GUIDE
  • JG.1 Getting Started With Jmp
  • JG.2 Entering Data
  • JG.3 Create New Project or Data Table
  • JG.4 Open or Save Files
  • JG.5 Print Data Tables or Report Windows
  • JG.6 Jmp Script Files
  • MINITAB GUIDE
  • MG.1 Getting Started with Minitab
  • MG.2 Entering Data
  • MG.3 Open or Save Files
  • MG.4 Insert or Copy Worksheets
  • MG.5 Print Worksheets
  • TABLEAU GUIDE
  • TG.1 Getting Started with Tableau
  • TG.2 Entering Data
  • TG.3 Open or Save a Workbook
  • TG.4 Working with Data
  • TG.5 Print a Workbook
  • 1 Defining and Collecting Data
  • USING STATISTICS: Defining Moments
  • 1.1 Defining Variables
  • Classifying Variables by Type
  • Measurement Scales
  • 1.2 Collecting Data
  • Populations and Samples
  • Data Sources
  • 1.3 Types of Sampling Methods
  • Simple Random Sample
  • Systematic Sample
  • Stratified Sample
  • Cluster Sample
  • 1.4 Data Cleaning
  • Invalid Variable Values
  • Coding Errors
  • Data Integration Errors
  • Missing Values
  • Algorithmic Cleaning of Extreme Numerical Values
  • 1.5 Other Data Preprocessing Tasks
  • Data Formatting
  • Stacking and Unstacking Data
  • Recoding Variables
  • 1.6 Types of Survey Errors
  • Coverage Error
  • Nonresponse Error
  • Sampling Error
  • Measurement Error
  • Ethical Issues About Surveys
  • CONSIDER THIS: New Media Surveys/Old Survey Errors
  • USING STATISTICS: Defining Moments, Revisited
  • SUMMARY
  • REFERENCES
  • KEY TERMS
  • CHECKING YOUR UNDERSTANDING
  • CHAPTER REVIEW PROBLEMS
  • CASES FOR Chapter 1
  • Managing Ashland MultiComm Services
  • CardioGood Fitness
  • Clear Mountain State Student Survey
  • Learning with the Digital Cases
  • Chapter 1 EXCEL GUIDE
  • EG1.1 Defining Variables
  • EG1.2 Collecting Data
  • EG1.3 Types of Sampling Methods
  • EG1.4 Data Cleaning
  • EG1.5 Other Data Preprocessing
  • Chapter 1 JMP GUIDE
  • JG1.1 Defining Variables
  • JG1.2 Collecting Data
  • JG1.3 Types of Sampling Methods
  • JG1.4 Data Cleaning
  • JG1.5 Other Preprocessing Tasks
  • Chapter 1 MINITAB GUIDE
  • MG1.1 Defining Variables
  • MG1.2 Collecting Data
  • MG1.3 Types of Sampling Methods
  • MG1.4 Data Cleaning
  • MG1.5 Other Preprocessing Tasks
  • Chapter 1 TABLEAU GUIDE
  • TG1.1 Defining Variables
  • TG1.2 Collecting Data
  • TG1.3 Types of Sampling Methods
  • TG1.4 Data Cleaning
  • TG1.5 Other Preprocessing Tasks
  • 2 Organizing and Visualizing Variables
  • USING STATISTICS: “The Choice Is Yours”
  • 2.1 Organizing Categorical Variables
  • The Summary Table
  • The Contingency Table
  • 2.2 Organizing Numerical Variables
  • The Frequency Distribution
  • The Relative Frequency Distribution and the Percentage Distribution
  • The Cumulative Distribution
  • 2.3 Visualizing Categorical Variables
  • The Bar Chart
  • The Pie Chart and the Doughnut Chart
  • The Pareto Chart
  • Visualizing Two Categorical Variables
  • 2.4 Visualizing Numerical Variables
  • The Stem-and-Leaf Display
  • The Histogram
  • The Percentage Polygon
  • The Cumulative Percentage Polygon (Ogive)
  • 2.5 Visualizing Two Numerical Variables
  • The Scatter Plot
  • The Time-Series Plot
  • 2.6 Organizing a Mix of Variables
  • Drill-down
  • 2.7 Visualizing a Mix of Variables
  • Colored Scatter Plot
  • Bubble Charts
  • PivotChart (Excel)
  • Treemap (Excel, JMP, Tableau)
  • Sparklines (Excel, Tableau)
  • 2.8 Filtering and Querying Data
  • Excel Slicers
  • 2.9 Pitfalls in Organizing and Visualizing Variables
  • Obscuring Data
  • Creating False Impressions
  • Chartjunk
  • USING STATISTICS: “The Choice Is Yours,” Revisited
  • SUMMARY
  • REFERENCES
  • KEY EQUATIONS
  • KEY TERMS
  • CHECKING YOUR UNDERSTANDING
  • CHAPTER REVIEW PROBLEMS
  • CASES for Chapter 2
  • Managing Ashland MultiComm Services
  • Digital Case
  • CardioGood Fitness
  • The Choice Is Yours Follow-Up
  • Clear Mountain State Student Survey
  • Chapter 2 EXCEL GUIDE
  • EG2.1 Organizing Categorical Variables
  • EG2.2 Organizing Numerical Variables
  • EG2 Charts Group Reference
  • EG2.3 Visualizing Categorical Variables
  • EG2.4 Visualizing Numerical Variables
  • EG2.5 Visualizing Two Numerical Variables
  • EG2.6 Organizing a Mix of Variables
  • EG2.7 Visualizing a Mix of Variables
  • EG2.8 Filtering and Querying Data
  • Chapter 2 JMP GUIDE
  • JG2 JMP Choices for Creating Summaries
  • JG2.1 Organizing Categorical Variables
  • JG2.2 Organizing Numerical Variables
  • JG2.3 Visualizing Categorical Variables
  • JG2.4 Visualizing Numerical Variables
  • JG2.5 Visualizing Two Numerical Variables
  • JG2.6 Organizing a Mix of Variables
  • JG2.7 Visualizing a Mix of Variables
  • JG2.8 Filtering and Querying Data
  • JMP Guide Gallery
  • Chapter 2 MINITAB GUIDE
  • MG2.1 Organizing Categorical Variables
  • MG2.2 Organizing Numerical Variables
  • MG2.3 Visualizing Categorical Variables
  • MG2.4 Visualizing Numerical Variables
  • MG2.5 Visualizing Two Numerical Variables
  • MG2.6 Organizing a Mix of Variables
  • MG2.7 Visualizing a Mix of Variables
  • MG2.8 Filtering and Querying Data
  • Chapter 2 TABLEAU GUIDE
  • TG2.1 Organizing Categorical Variables
  • TG2.2 Organizing Numerical Variables
  • TG2.3 Visualizing Categorical Variables
  • TG2.4 Visualizing Numerical Variables
  • TG2.5 Visualizing Two Numerical Variables
  • TG2.6 Organizing a Mix of Variables
  • TG2.7 Visualizing a Mix of Variables
  • 3 Numerical Descriptive Measures
  • USING STATISTICS: More Descriptive Choices
  • 3.1 Measures of Central Tendency
  • The Mean
  • The Median
  • The Mode
  • 3.2 Measures of Variation and Shape
  • The Range
  • The Variance and the Standard Deviation
  • The Coefficient of Variation
  • Z Scores
  • Shape: Skewness
  • Shape: Kurtosis
  • 3.3 Exploring Numerical Variables
  • Quartiles
  • The Interquartile Range
  • The Five-Number Summary
  • The Boxplot
  • 3.4 Numerical Descriptive Measures for a Population
  • The Population Mean
  • The Population Variance and Standard Deviation
  • The Empirical Rule
  • Chebyshev’s Theorem
  • 3.5 The Covariance and the Coefficient of Correlation
  • The Covariance
  • The Coefficient of Correlation
  • 3.6 Descriptive Statistics: Pitfalls and Ethical Issues
  • USING STATISTICS: More Descriptive Choices, Revisited
  • SUMMARY
  • REFERENCES
  • KEY EQUATIONS
  • KEY TERMS
  • CHECKING YOUR UNDERSTANDING
  • CHAPTER REVIEW PROBLEMS
  • CASES FOR CHAPTER 3
  • Managing Ashland MultiComm Services
  • Digital Case
  • CardioGood Fitness
  • More Descriptive Choices Follow-up
  • Clear Mountain State Student Survey
  • Chapter 3 EXCEL GUIDE
  • EG3.1 Measures of Central Tendency
  • EG3.2 Measures of Variation and Shape
  • EG3.3 Exploring Numerical Variables
  • EG3.4 Numerical Descriptive Measures for a Population
  • EG3.5 The Covariance and the Coefficient of Correlation
  • Chapter 3 JMP GUIDE
  • JG3.1 Measures of Central Tendency
  • JG3.2 Measures of Variation and Shape
  • JG3.3 Exploring Numerical Variables
  • JG3.4 Numerical Descriptive Measures for a Population
  • JG3.5 The Covariance and the Coefficient of Correlation
  • Chapter 3 MINITAB GUIDE
  • MG3.1 Measures of Central Tendency
  • MG3.2 Measures of Variation and Shape
  • MG3.3 Exploring Numerical Variables
  • MG3.4 Numerical Descriptive Measures for a Population
  • MG3.5 The Covariance and the Coefficient of Correlation
  • Chapter 3 TABLEAU GUIDE
  • TG3.3 Exploring Numerical Variables
  • 4 Basic Probability
  • USING STATISTICS: Possibilities at M&R Electronics World
  • 4.1 Basic Probability Concepts
  • Events and Sample Spaces
  • Types of Probability
  • Summarizing Sample Spaces
  • Simple Probability
  • Joint Probability
  • Marginal Probability
  • General Addition Rule
  • 4.2 Conditional Probability
  • Calculating Conditional Probabilities
  • Decision Trees
  • Independence
  • Multiplication Rules
  • Marginal Probability Using the General Multiplication Rule
  • 4.3 Ethical Issues and Probability
  • 4.4 Bayes’ Theorem
  • CONSIDER THIS: Divine Providence and Spam
  • 4.5 Counting Rules
  • USING STATISTICS: Possibilities at M&R Electronics World, Revisited
  • SUMMARY
  • REFERENCES
  • KEY EQUATIONS
  • KEY TERMS
  • CHECKING YOUR UNDERSTANDING
  • CHAPTER REVIEW PROBLEMS
  • CASES FOR CHAPTER 4
  • Digital Case
  • CardioGood Fitness
  • The Choice Is Yours Follow-Up
  • Clear Mountain State Student Survey
  • Chapter 4 EXCEL GUIDE
  • EG4.1 Basic Probability Concepts
  • EG4.4 Bayes’ Theorem
  • EG4.5 Counting Rules
  • Chapter 4 JMP GUIDE
  • JG4.4 Bayes’ Theorem
  • Chapter 4 MINITAB GUIDE
  • MG4.5 Counting Rules
  • 5 Discrete Probability Distributions
  • USING STATISTICS: Events of Interest at Ricknel Home Centers
  • 5.1 The Probability Distribution for a Discrete Variable
  • Expected Value of a Discrete Variable
  • Variance and Standard Deviation of a Discrete Variable
  • 5.2 Binomial Distribution
  • Histograms for Discrete Variables
  • Summary Measures for the Binomial Distribution
  • 5.3 Poisson Distribution
  • USING STATISTICS: Events of Interest, Revisited
  • SUMMARY
  • REFERENCES
  • KEY EQUATIONS
  • KEY TERMS
  • CHECKING YOUR UNDERSTANDING
  • CHAPTER REVIEW PROBLEMS
  • CASES FOR CHAPTER 5
  • Managing Ashland MultiComm Services
  • Digital Case
  • Chapter 5 EXCEL GUIDE
  • EG5.1 The Probability Distribution for a Discrete Variable
  • EG5.2 Binomial Distribution
  • EG5.3 Poisson Distribution
  • Chapter 5 JMP GUIDE
  • JG5.1 The Probability Distribution for a Discrete Variable
  • JG5.2 Binomial Distribution
  • JG5.3 Poisson Distribution
  • Chapter 5 MINITAB GUIDE
  • MG5.1 The Probability Distribution for a Discrete Variable
  • MG5.2 Binomial Distribution
  • MG5.3 Poisson Distribution
  • 6 The Normal Distribution
  • USING STATISTICS: Normal Load Times at MyTVLab
  • 6.1 Continuous Probability Distributions
  • 6.2 The Normal Distribution
  • Role of the Mean and the Standard Deviation
  • Calculating Normal Probabilities
  • Finding X Values
  • CONSIDER THIS: What Is Normal?
  • 6.3 Evaluating Normality
  • Comparing Data Characteristics to Theoretical Properties
  • Constructing the Normal Probability Plot
  • USING STATISTICS: Normal Load Times, Revisited
  • SUMMARY
  • REFERENCES
  • KEY EQUATIONS
  • KEY TERMS
  • CHECKING YOUR UNDERSTANDING
  • CHAPTER REVIEW PROBLEMS
  • CASES FOR CHAPTER 6
  • Managing Ashland MultiComm Services
  • CardioGood Fitness
  • More Descriptive Choices Follow-up
  • Clear Mountain State Student Survey
  • Digital Case
  • Chapter 6 EXCEL GUIDE
  • EG6.2 The Normal Distribution
  • EG6.3 Evaluating Normality
  • Chapter 6 JMP GUIDE
  • JG6.2 The Normal Distribution
  • JG6.3 Evaluating Normality
  • Chapter 6 MINITAB GUIDE
  • MG6.2 The Normal Distribution
  • MG6.3 Evaluating Normality
  • 7 Sampling Distributions
  • USING STATISTICS: Sampling Oxford Cereals
  • 7.1 Sampling Distributions
  • 7.2 Sampling Distribution of the Mean
  • The Unbiased Property of the Sample Mean
  • Standard Error of the Mean
  • Sampling from Normally Distributed Populations
  • Sampling from Non-normally Distributed Populations—The Central Limit Theorem
  • VISUAL EXPLORATIONS: Exploring Sampling Distributions
  • 7.3 Sampling Distribution of the Proportion
  • USING STATISTICS: Sampling Oxford Cereals, Revisited
  • SUMMARY
  • REFERENCES
  • KEY EQUATIONS
  • KEY TERMS
  • CHECKING YOUR UNDERSTANDING
  • CHAPTER REVIEW PROBLEMS
  • CASES FOR CHAPTER 7
  • Managing Ashland MultiComm Services
  • Digital Case
  • Chapter 7 EXCEL GUIDE
  • EG7.2 Sampling Distribution of the Mean
  • Chapter 7 JMP GUIDE
  • JG7.2 Sampling Distribution of the Mean
  • Chapter 7 MINITAB GUIDE
  • MG7.2 Sampling Distribution of the Mean
  • 8 Confidence Interval Estimation
  • USING STATISTICS: Getting Estimates at Ricknel Home Centers
  • 8.1 Confidence Interval Estimate for the Mean (σ Known)
  • Sampling Error
  • Can You Ever Know the Population Standard Deviation?
  • 8.2 Confidence Interval Estimate for the Mean (σ Unknown)
  • Student’s t Distribution
  • The Concept of Degrees of Freedom
  • Properties of the t Distribution
  • The Confidence Interval Statement
  • 8.3 Confidence Interval Estimate for the Proportion
  • 8.4 Determining Sample Size
  • Sample Size Determination for the Mean
  • Sample Size Determination for the Proportion
  • 8.5 Confidence Interval Estimation and Ethical Issues
  • USING STATISTICS: Getting Estimates at Ricknel Home Centers, Revisited
  • SUMMARY
  • REFERENCES
  • KEY EQUATIONS
  • KEY TERMS
  • CHECKING YOUR UNDERSTANDING
  • CHAPTER REVIEW PROBLEMS
  • CASES FOR CHAPTER 8
  • Managing Ashland MultiComm Services
  • Digital Case
  • Sure Value Convenience Stores
  • CardioGood Fitness
  • More Descriptive Choices Follow-Up
  • Clear Mountain State Student Survey
  • Chapter 8 EXCEL GUIDE
  • EG8.1 Confidence Interval Estimate for the Mean (σ Known)
  • EG8.2 Confidence Interval Estimate for the Mean (σ Unknown)
  • EG8.3 Confidence Interval Estimate for the Proportion
  • EG8.4 Determining Sample Size
  • Chapter 8 JMP GUIDE
  • JG8.1 Confidence Interval Estimate for the Mean ( σ Known)
  • JG8.2 Confidence Interval Estimate for the Mean ( σ Unknown)
  • JG8.3 Confidence Interval Estimate for the Proportion
  • JG8.4 Determining Sample Size
  • Chapter 8 MINITAB GUIDE
  • MG8.1 Confidence Interval Estimate for the Mean (σ Known)
  • MG8.2 Confidence Interval Estimate for the Mean (σ Unknown)
  • MG8.3 Confidence Interval Estimate for the Proportion
  • MG8.4 Determining Sample Size
  • 9 Fundamentals of Hypothesis Testing: One-Sample Tests
  • USING STATISTICS: Significant Testing at Oxford Cereals
  • 9.1 Fundamentals of Hypothesis Testing
  • The Critical Value of the Test Statistic
  • Regions of Rejection and Nonrejection
  • Risks in Decision Making Using Hypothesis Testing
  • Z Test for the Mean (σ Known)
  • Hypothesis Testing Using the Critical Value Approach
  • Hypothesis Testing Using the p-Value Approach
  • A Connection Between Confidence Interval Estimation and Hypothesis Testing
  • Can You Ever Know the Population Standard Deviation?
  • 9.2 t Test of Hypothesis for the Mean (σ Unknown)
  • Using the Critical Value Approach
  • Using the p-Value Approach
  • Checking the Normality Assumption
  • 9.3 One-Tail Tests
  • Using the Critical Value Approach
  • Using the p-Value Approach
  • 9.4 Z Test of Hypothesis for the Proportion
  • Using the Critical Value Approach
  • Using the p-Value Approach
  • 9.5 Potential Hypothesis-Testing Pitfalls and Ethical Issues
  • Important Planning Stage Questions
  • Statistical Significance Versus Practical Significance
  • Statistical Insignificance Versus Importance
  • Reporting of Findings
  • Ethical Issues
  • USING STATISTICS: Significant Testing..., Revisited
  • SUMMARY
  • REFERENCES
  • KEY EQUATIONS
  • KEY TERMS
  • CHECKING YOUR UNDERSTANDING
  • CHAPTER REVIEW PROBLEMS
  • CASES FOR CHAPTER 9
  • Managing Ashland MultiComm Services
  • Digital Case
  • Sure Value Convenience Stores
  • Chapter 9 EXCEL GUIDE
  • EG9.1 Fundamentals of Hypothesis Testing
  • EG9.2 t Test of Hypothesis for the Mean (σ Unknown)
  • EG9.3 One-Tail Tests
  • EG9.4 Z Test of Hypothesis for the Proportion
  • Chapter 9 JMP GUIDE
  • JG9.1 Fundamentals of Hypothesis Testing
  • JG9.2 t Test of Hypothesis for the Mean (σ Unknown)
  • JG9.3 One-Tail Tests
  • JG9.4 Z Test of Hypothesis for the Proportion
  • Chapter 9 MINITAB GUIDE
  • MG9.1 Fundamentals of Hypothesis Testing
  • MG9.2 t Test of Hypothesis for the Mean (σ Unknown)
  • MG9.3 One-Tail Tests
  • MG9.4 Z Test of Hypothesis for the Proportion
  • 10 Two-Sample Tests and One-Way ANOVA
  • USING STATISTICS I: Differing Means for Selling Streaming Media Players at Arlingtons?
  • 10.1 Comparing the Means of Two Independent Populations
  • Pooled-Variance t Test for the Difference Between Two Means Assuming Equal Variances
  • Evaluating the Normality Assumption
  • Confidence Interval Estimate for the Difference Between Two Means
  • Separate-Variance t Test for the Difference Between Two Means, Assuming Unequal Variances
  • CONSIDER THIS: Do People Really Do This?
  • 10.2 Comparing the Means of Two Related Populations
  • Paired t Test
  • Confidence Interval Estimate for the Mean Difference
  • 10.3 Comparing the Proportions of Two Independent Populations
  • Z Test for the Difference Between Two Proportions
  • Confidence Interval Estimate for the Difference Between Two Proportions
  • 10.4 F Test for the Ratio of Two Variances
  • USING STATISTICS II: The Means to Find Differences at Arlingtons
  • 10.5 One-Way ANOVA
  • Analyzing Variation in One-Way ANOVA
  • F Test for Differences Among More Than Two Means
  • One-Way ANOVA F Test Assumptions
  • Levene Test for Homogeneity of Variance
  • Multiple Comparisons: The Tukey-Kramer Procedure
  • USING STATISTICS I: Differing Means for Selling, Revisited
  • USING STATISTICS II: The Means to Find Differences at Arlingtons, Revisited
  • SUMMARY
  • REFERENCES
  • KEY EQUATIONS
  • KEY TERMS
  • CHECKING YOUR UNDERSTANDING
  • CHAPTER REVIEW PROBLEMS
  • CASES FOR CHAPTER 10
  • Managing Ashland MultiComm Services
  • Digital Case
  • Sure Value Convenience Stores
  • CardioGood Fitness
  • More Descriptive Choices Follow-Up
  • Clear Mountain State Student Survey
  • Chapter 10 EXCEL GUIDE
  • EG10.1 Comparing the Means of Two Independent Populations
  • EG10.2 Comparing the Means of Two Related Populations
  • EG10.3 Comparing the Proportions of Two Independent Populations
  • EG10.4 F Test for the Ratio of Two Variances
  • EG10.5 One-Way Anova
  • Chapter 10 JMP GUIDE
  • JG10.1 Comparing the Means of Two Independent Populations
  • JG10.2 Comparing the Means of Two Related Populations
  • JG10.3 Comparing the Proportions of Two Independent Populations
  • JG10.4 F Test for the Ratio of Two Variances
  • JG10.5 One-Way Anova
  • Chapter 10 MINITAB GUIDE
  • MG10.1 Comparing the Means of Two Independent Populations
  • MG10.2 Comparing the Means of Two Related Populations
  • MG10.3 Comparing the Proportions of Two Independent Populations
  • MG10.4 F Test for the Ratio of Two Variances
  • MG10.5 One-Way Anova
  • 11 Chi-Square Tests
  • USING STATISTICS: Avoiding Guesswork About Resort Guests
  • 11.1 Chi-Square Test for the Difference Between Two Proportions
  • 11.2 Chi-Square Test for Differences Among More Than Two Proportions
  • 11.3 Chi-Square Test of Independence
  • USING STATISTICS: Avoiding Guesswork, Revisited
  • SUMMARY
  • REFERENCES
  • KEY EQUATIONS
  • KEY TERMS
  • CHECKING YOUR UNDERSTANDING
  • CHAPTER REVIEW PROBLEMS
  • CASES FOR CHAPTER 11
  • Managing Ashland MultiComm Services
  • PHASE 1
  • PHASE 2
  • Digital Case
  • CardioGood Fitness
  • Clear Mountain State Student Survey
  • Chapter 11 EXCEL GUIDE
  • EG11.1 Chi-Square Test for the Difference Between Two Proportions
  • EG11.2 Chi-Square Test for Differences Among More Than Two Proportions
  • EG11.3 Chi-Square Test of Independence
  • Chapter 11 JMP GUIDE
  • JG11.1 Chi-Square Test for the Difference Between Two Proportions
  • JG11.2 Chi-Square Test for Difference Among More Than Two Proportions
  • JG11.3 Chi-Square Test of Independence
  • Chapter 11 MINITAB GUIDE
  • MG11.1 Chi-Square Test for the Difference Between Two Proportions
  • MG11.2 Chi-Square Test for Differences Among More Than Two Proportions
  • MG11.3 Chi-Square Test of Independence
  • 12 Simple Linear Regression
  • USING STATISTICS: Knowing Customers at Sunflowers Apparel
  • Preliminary Analysis
  • 12.1 Simple Linear Regression Models
  • 12.2 Determining the Simple Linear Regression Equation
  • The Least-Squares Method
  • Predictions in Regression Analysis: Interpolation Versus Extrapolation
  • Calculating the Slope, b1, and the Y Intercept, b0
  • 12.3 Measures of Variation
  • Computing the Sum of Squares
  • The Coefficient of Determination
  • Standard Error of the Estimate
  • 12.4 Assumptions of Regression
  • 12.5 Residual Analysis
  • Evaluating the Assumptions
  • 12.6 Measuring Autocorrelation: The Durbin-Watson Statistic
  • Residual Plots to Detect Autocorrelation
  • The Durbin-Watson Statistic
  • 12.7 Inferences About the Slope and Correlation Coefficient
  • t Test for the Slope
  • F Test for the Slope
  • Confidence Interval Estimate for the Slope
  • t Test for the Correlation Coefficient
  • 12.8 Estimation of Mean Values and Prediction of Individual Values
  • The Confidence Interval Estimate for the Mean Response
  • The Prediction Interval for an Individual Response
  • 12.9 Potential Pitfalls in Regression
  • USING STATISTICS: Knowing Customers, Revisited
  • SUMMARY
  • REFERENCES
  • KEY EQUATIONS
  • KEY TERMS
  • CHECKING YOUR UNDERSTANDING
  • CHAPTER REVIEW PROBLEMS
  • CASES FOR CHAPTER 12
  • Managing Ashland MultiComm Services
  • Digital Case
  • Brynne Packaging
  • Chapter 12 EXCEL GUIDE
  • EG12.2 Determining the Simple Linear Regression Equation
  • EG12.3 Measures of Variation
  • EG12.5 Residual Analysis
  • EG12.6 Measuring Autocorrelation: the Durbin‐Watson Statistic
  • EG12.7 Inferences About the Slope and Correlation Coefficient
  • EG12.8 Estimation of Mean Values and Prediction of Individual Values
  • Chapter 12 JMP GUIDE
  • JG12.2 Determining the Simple Linear Regression Equation
  • JG12.3 Measures of Variation
  • JG12.5 Residual Analysis
  • JG12.6 Measuring Autocorrelation: the Durbin‐Watson Statistic
  • JG12.7 Inferences About the Slope and Correlation Coefficient
  • JG12.8 Estimation of Mean Values and Prediction of Individual Values
  • Chapter 12 MINITAB GUIDE
  • MG12.2 Determining the Simple Linear Regression Equation
  • MG12.3 Measures of Variation
  • MG12.5 Residual Analysis
  • MG12.6 Measuring Autocorrelation: The Durbin‐Watson Statistic
  • MG12.7 Inferences About the Slope and Correlation Coefficient
  • MG12.8 Estimation of Mean Values and Prediction of Individual Values
  • Chapter 12 TABLEAU GUIDE
  • TG12.2 Determining the Simple Linear Regression Equation
  • TG12.3 Measures of Variation
  • 13 Multiple Regression
  • USING STATISTICS: The Multiple Effects of OmniPower Bars
  • 13.1 Developing a Multiple Regression Model
  • Interpreting the Regression Coefficients
  • Predicting the Dependent Variable Y
  • 13.2 Evaluating Multiple Regression Models
  • Coefficient of Multiple Determination, r²
  • Adjusted r²
  • F Test for the Significance of the Overall Multiple Regression Model
  • 13.3 Multiple Regression Residual Analysis
  • 13.4 Inferences About the Population Regression Coefficients
  • Tests of Hypothesis
  • Confidence Interval Estimation
  • 13.5 Using Dummy Variables and Interaction Terms
  • Interactions
  • USING STATISTICS: The Multiple Effects, Revisited
  • SUMMARY
  • REFERENCES
  • KEY EQUATIONS
  • KEY TERMS
  • CHECKING YOUR UNDERSTANDING
  • CHAPTER REVIEW PROBLEMS
  • CASES FOR CHAPTER 13
  • Managing Ashland MultiComm Services
  • Digital Case
  • CHAPTER 13 EXCEL GUIDE
  • EG13.1 Developing a Multiple Regression Model
  • EG13.2 Evaluating Multiple Regression Models
  • EG13.3 Multiple Regression ‐Residual Analysis
  • EG13.4 Inferences About the Population Regression Coefficients
  • EG13.5 Using Dummy Variables and Interaction Terms
  • CHAPTER 13 JMP GUIDE
  • JG13.1 Developing a Multiple Regression Model
  • JG13.2 Evaluating Multiple Regression Models
  • JG13.3 Multiple Regression Residual Analysis
  • JG13.4 Inferences About the Population
  • JG13.5 Using Dummy Variables And Interaction Terms
  • CHAPTER 13 MINITAB GUIDE
  • MG13.1 Developing a Multiple Regression Model
  • MG13.2 Evaluating Multiple Regression Models
  • MG13.3 Multiple Regression ‐Residual Analysis
  • MG13.4 Inferences About the Population Regression Coefficients
  • MG13.5 Using Dummy Variables and Interaction Terms In Regression Models
  • 14 Business Analytics
  • USING STATISTICS: Back to Arlingtons for the Future
  • 14.1 Business Analytics Categories
  • Inferential Statistics and Predictive Analytics
  • Supervised and Unsupervised Methods
  • CONSIDER THIS: What’s My Major If I Want to Be a Data Miner?
  • 14.2 Descriptive Analytics
  • Dashboards
  • Data Dimensionality and Descriptive Analytics
  • 14.3 Predictive Analytics for Prediction
  • 14.4 Predictive Analytics for Classification
  • 14.5 Predictive Analytics for Clustering
  • 14.6 Predictive Analytics for Association
  • Multidimensional Scaling (MDS)
  • 14.7 Text Analytics
  • 14.8 Prescriptive Analytics
  • USING STATISTICS: Back to Arlingtons... , Revisited
  • REFERENCES
  • KEY EQUATIONS
  • KEY TERMS
  • CHECKING YOUR UNDERSTANDING
  • CHAPTER REVIEW PROBLEMS
  • CHAPTER 14 SOFTWARE GUIDE
  • Introduction
  • SG14.2 Descriptive Analytics
  • SG14.3 Predictive Analytics for Prediction
  • SG14.4 Predictive Analytics for Classification
  • SG14.5 Predictive Analytics for Clustering
  • SG14.6 Predictive Analytics for Association
  • Appendices
  • A. Basic Math Concepts and Symbols
  • A.1 Operators
  • A.2 Rules for Arithmetic Operations
  • A.3 Rules for Algebra: Exponents and Square Roots
  • A.4 Rules for Logarithms
  • A.5 Summation Notation
  • A.6 Greek Alphabet
  • B. IMPORTANT SOFTWARE SKILLS AND CONCEPTS
  • B.1 Identifying the Software Version
  • B.2 Formulas
  • B.3 Excel Cell References
  • B.4 Excel Worksheet Formatting
  • B.5E Excel Chart Formatting
  • B.5J JMP Chart Formatting
  • B.5M Minitab Chart Formatting
  • B.5T Tableau Chart Formatting
  • B.6 Creating Histograms for Discrete Probability Distributions (Excel)
  • B.7 Deleting the “Extra” Histogram Bar (Excel)
  • C. ONLINE RESOURCES
  • C.1 About the Online Resources for This Book
  • C.2 Data Files
  • C.3 Files Integrated With Microsoft Excel
  • C.4 Supplemental Files
  • D. CONFIGURING SOFTWARE
  • D.1 Microsoft Excel Configuration
  • D.2 JMP Configuration
  • D.3 Minitab Configuration
  • D.4 Tableau Configuration
  • E. TABLE
  • E.1 Table of Random Numbers
  • E.2 The Cumulative Standardized Normal Distribution
  • E.3 Critical Values of t
  • E.4 Critical Values of X2
  • E.5 Critical Values of F
  • E.6 The Standardized Normal Distribution
  • E.7 Critical Values of the Studentized Range, Q
  • E.8 Critical Values, dL and dU, of the Durbin-Watson Statistic, D (Critical Values Are One-Sided)
  • E.9 Control Chart Factors
  • F. USEFUL KNOWLEDGE
  • F.1 Keyboard Shortcuts
  • F.2 Understanding the Nonstatistical Functions
  • G. SOFTWARE FAQS
  • G.1 Microsoft Excel FAQs
  • G.2 PHStat FAQs
  • G.3 JMP FAQs
  • G.4 Minitab FAQs
  • G.5 Tableau FAQs
  • H. ALL ABOUT PHStat
  • H.1 What is PHStat?
  • H.2 Obtaining and Setting Up PHStat
  • H.3 Using PHStat
  • H.4 PHStat Procedures, by Category
  • Self-Test Solutions and Answers to Selected Even-Numbered Problems
  • Index
  • A
  • B
  • C
  • D
  • E
  • F
  • G
  • H
  • I
  • J
  • K
  • L
  • M
  • N
  • O
  • P
  • Q
  • R
  • S
  • T
  • U
  • V
  • W
  • Y
  • Z
  • Credits