Business Statistics: A First Course

Cover
Dedication
About the Authors
Brief Contents
Contents
Preface
Getting Started: Important Things to Learn First
	Using Statistics: “You Cannot Escape from Data”
	GS.1 Statistics: A Way of Thinking
	GS.2 Data: What is it?
		Statistics
	GS.3 The Changing Face of Statistics
		Business Analytics
		“Big Data”
		Integral Role of Software in Statistics
	GS.4 Statistics: An Important Part of Your Business Education
		Making Best Use of This Book
		Making Best Use of the Software Guides
	References
	Key Terms
	Excel Guide
		EG.1 Getting Started with Microsoft Excel
		EG.2 Entering Data
	Minitab Guide
		MG.1 Getting Started with Minitab
		MG.2 Entering Data
Chapter 1: Defining and Collecting Data
	Using Statistics: Beginning of the End … Or the End of the Beginning?
	1.1 Defining Variables
		Classifying Variables by Type
	1.2 Collecting Data
		Data Sources
		Populations and Samples
		Structured Versus Unstructured Data
		Electronic Formats and Encodings
		Data Cleaning
		Recoding Variables
	1.3 Types of Sampling Methods
		Simple Random Sample
		Systematic Sample
		Stratified Sample
		Cluster Sample
	1.4 Types of Survey Errors
		Coverage Error
		Nonresponse Error
		Sampling Error
		Measurement Error
		Ethical Issues About Surveys
	Think About This: New Media Surveys/Old Sampling Problems
	Using Statistics: Beginning of the End… Revisited
	Summary
	References
	Key Terms
	Checking Your Understanding
	Chapter Review Problems
	Cases for Chapter1
		Managing Ashland MultiComm Services
		CardioGood Fitness
		Clear Mountain State Student Surveys
		Learning with the Digital Cases
	Chapter 1 Excel Guide
		EG1.1 Defining Variables
		EG1.2 Collecting Data
		EG1.3 Types of Sampling Methods
	Chapter 1 Minitab Guide
		MG1.1 Defining Variables
		MG1.2 Collecting Data
		MG1.3 Types of Sampling Methods
Chapter 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 Ordered Array
		The Frequency Distribution
		Classes and Excel Bins
		The Relative Frequency Distribution and the Percentage Distribution
		The Cumulative Distribution
		Stacked and Unstacked Data
	2.3 Visualizing Categorical Variables
		The Bar Chart
		The Pie Chart
		The Pareto Chart
		The Side-by-Side Bar Chart
	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 and Visualizing a Set of Variables
		Multidimensional Contingency Tables
		Data Discovery
	2.7 The Challenge in Organizing and Visualizing Variables
		Obscuring Data
		Creating False Impressions
		Chartjunk
		Best Practices for Constructing Visualizations
	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 Surveys
	Chapter 2 Excel Guide
		EG2.1 Organizing Categorical Variables
		EG2.2 Organizing Numerical Variables
		EG2.3 Visualizing Categorical Variables
		EG2.4 Visualizing Numerical Variables
		EG2.5 Visualizing Two Numerical Variables
		EG2.6 Organizing and Visualizing a Set of Variables
	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 and Visualizing a Set of Variables
Chapter 3: Numerical Descriptive Measures
	Using Statistics: More Descriptive Choices
	3.1 Central Tendency
		The Mean
		The Median
		The Mode
	3.2 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 Data
		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
		The Chebyshev Rule
	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 Surveys
	Chapter 3 Excel Guide
		EG3.1 Central Tendency
		EG3.2 Variation and Shape
		EG3.3 Exploring Numerical Data
		EG3.4 Numerical Descriptive Measures for a Population
		EG3.5 The Covariance and the Coefficient of Correlation
	Chapter 3 Minitab Guide
		MG3.1 Central Tendency
		MG3.2 Variation and Shape
		MG3.3 Exploring Numerical Data
		MG3.4 Numerical Descriptive Measures for a Population
		MG3.5 The Covariance and the Coefficient of Correlation
Chapter 4: Basic Probability
	Using Statistics: Possibilities at M&R Electronics World
	4.1 Basic Probability Concepts
		Events and Sample Spaces
		Contingency Tables and Venn Diagrams
		Simple Probability
		Joint Probability
		Marginal Probability
		General Addition Rule
	4.2 Conditional Probability
		Computing Conditional Probabilities
		Decision Trees
		Independence
		Multiplication Rules
		Marginal Probability Using the General Multiplication Rule
	4.3 Bayes’ Theorem
	Think About This Divine Providence and Spam
	4.4 Counting Rules
	4.5 Ethical Issues and Probability
	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
		Clear Mountain State Student Surveys
	Chapter 4 Excel Guide
		EG4.1 Basic Probability Concepts
		EG4.2 Conditional Probability
		EG4.3 Bayes’ Theorem
		EG4.4 Counting Rules
	Chapter 4 Minitab Guide
		MG4.1 Basic Probability Concepts
		MG4.2 Conditional Probability
		MG4.3 Bayes’ Theorem
		MG4.4 Counting Rules
Chapter 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
	5.3 Poisson Distribution
	Using Statistics: Events of Interest at Ricknel Home Centers, 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 Minitab Guide
	MG5.1 The Probability Distribution for a Discrete Variable
	MG5.2 B inomial Distribution
	MG5.3 Poisson Distribution
Chapter 6: The Normal Distribution
	Using Statistics: Normal Downloading at MyTVLab
	6.1 Continuous Probability Distributions
	6.2 The Normal Distribution
		Computing Normal Probabilities
		Finding X Values
	Visual Explorations: Exploring the Normal Distribution
	Think About This What is Normal?
	6.3 Evaluating Normality
		Comparing Data Characteristics to Theoretical Properties
		Constructing the Normal Probability Plot
	Using Statistics: Normal Downloading at MyTVLab, Revisited
	Summary
	References
	Key Equations
	Key Terms
	Checking Your Understanding
	Chapter Review Problems
	Cases for Chapter 6
		Managing Ashland MultiComm Services
		Digital Case
		CardioGood Fitness
		More Descriptive Choices Follow-up
		Clear Mountain State Student Surveys
	Chapter 6 Excel Guide
		EG6.1 Continuous Probability Distributions
		EG6.2 The Normal Distribution
		EG6.3 Evaluating Normality
	Chapter 6 Minitab Guide
		MG6.1 Continuous Probability Distributions
		MG6.2 The Normal Distribution
		MG6.3 Evaluating Normality
Chapter 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
		EG7.1 Sampling Distributions
		EG7.2 Sampling Distribution of the Mean
		EG7.3 Sampling Distribution of the Proportion
	Chapter 7 Minitab Guide
		MG7.1 Sampling Distributions
		MG7.2 Sampling Distribution of the Mean
		MG7.3 Sampling Distribution of the Proportion
Chapter 8: Confidence Interval Estimation
	Using Statistics: Getting Estimates at Ricknel Home Centers
	8.1 Confidence Interval Estimate for the Mean (σ Known)
		Can You Ever Know the Population Standard Deviation?
	8.2 Confidence Interval Estimate for the Mean (σ Unknown)
		Student’s t Distribution
		Properties of the t Distribution
		The Concept of Degrees of Freedom
		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
	8.6 Bootstrapping
	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 Surveys
	Chapter 8 Excel Guide
		EG8.1 Confidence Interval Estimate for the Mean (σ Known
		EG8.2 Confidence Interval Estimatefor the Mean (σ Unknown)
		EG8.3 Confidence Interval Estimate for the Proportion
		EG8.4 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
Chapter 9: Fundamentals of Hypothesis Testing: One-Sample Tests
	Using Statistics: Significant Testing at Oxford Cereals
	9.1 Fundamentals of Hypothesis-Testing Methodology
		The Null and Alternative Hypotheses
		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)
		The Critical Value Approach
		The p-Value Approach
		Checking the Normality Assumption
	9.3 One-Tail Tests
		The Critical Value Approach
		The p-Value Approach
	9.4 Z Test of Hypothesis for the Proportion
		The Critical Value Approach
		The p-Value Approach
	9.5 Potential Hypothesis-Testing Pitfalls and Ethical Issues
		Statistical Significance Versus Practical Significance
		Statistical Insignificance Versus Importance
		Reporting of Findings
		Ethical Issues
	Using Statistics: Significant Testing at Oxford Cereals, 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 Methodology
		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 Minitab Guide
		MG9.1 Fundamentals of Hypothesis-Testing Methodology
		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
Chapter 10: Two-Sample Tests and One-Way ANOVA
	Using Statistics: For North Fork, Are There Different Means to the Ends?
	10.1 Comparing the Means of Two Independent Populations
		Pooled-Variance t Test for the Difference Between Two Means
		Confidence Interval Estimate for the Difference Between Two Means
		t Test for the Difference Between Two Means, Assuming Unequal Variances
		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
	10.5 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
	10.6 Effect Size
	Using Statistics: For North Fork, Are There Different Means to the Ends? 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 Surveys
	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 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
Chapter 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 About Resort Guests, Revisited
	Summary
	References
	Key Equations
	Key Terms
	Checking Your Understanding
	Chapter Review Problems
	Cases for Chapter 11
		Managing Ashland MultiComm Services
		Digital Case
		CardioGood Fitness
		Clear Mountain State Student Surveys
	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 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
Chapter 12: Simple Linear Regression
	Using Statistics: Knowing Customers at Sunflowers Apparel
	12.1 Types of Regression Models
		Simple Linear Regression Models
	12.2 Determining the Simple Linear Regression Equation
		The Least-Squares Method
		Predictions in Regression Analysis: Interpolation Versus Extrapolation
		Computing the Y Intercept, b0, and the Slope, b1
		Visual Explorations: Exploring Simple Linear Regression Coefficients
	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
		Six Steps for Avoiding the Potential Pitfalls
	Using Statistics: Knowing Customers at Sunflowers Apparel, 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
		EG12.1 Types of Regression Models
		EG12.2 Determining the Simple Linear Regression Equation
		EG12.3 Measures of Variation
		EG12.4 Assumptions of Regression
		EG12.5 Residual Analysis
		EG12.6 Measuring Autocorrelation: the Durbin-Watson Statistic
		EG12.7 Inferences About the Slope and Correlation Coefficient
		EG 12.8 Estimation of Mean Values and Prediction of Individual Values
	Chapter 12 Minitab Guide
		MG12.1 Types of Regression Models
		MG12.2 Determining the Simple Linear Regression Equation
		MG12.3 Measures of Variation
		MG12.4 Assumptions
		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 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 r2, Adjusted r2, and the Overall F Test
		Coefficient of Multiple Determination
		Adjusted r2
		Test for the Significance of the Overall Multiple Regression Model
	13.3 Residual Analysis for the Multiple Regression Model
	13.4 Inferences Concerning the Population Regression Coefficients
		Tests of Hypothesis
		Confidence Interval Estimation
	13.5 Using Dummy Variables and Interaction Terms in Regression Models
		Dummy Variables
		Interactions
	Using Statistics: The Multiple Effects of OmniPower Bars, Revisited
	Summary
	References
	Key Equations
	Key Terms
	Checking Your Understanding
	Chapter Review Problems
	Cases for Chapter 13
		Managing Ashland MultiComm Services
		Digital Case
	Chapter13 Excel Guide
		EG13.1 Developing a Multiple Regression Model
		EG13.2 r2, Adjusted r2, and the Overall F Test
		EG13.3 Residual Analysis for the Multiple Regression Model
		EG13.4 Inferences Concerning the Population Regression Coefficients
		EG13.5 Using Dummy Variables and Interaction Terms in Regression Models
	Chapter 13 Minitab Guide
		MG13.1 Developing a Multiple Regression Model
		MG13.2 r2, Adjusted r2, and the Overall F Test
		MG13.3 Residual Analysis for the Multiple Regression Model
		MG13.4 Inferences Concerning the Population Regression Coefficients
		MG13.5 Using Dummy Variables and Interaction Terms in Regression Models
Chapter 14: Statistical Applications in Quality Management
	Using Statistics: Finding Quality at the Beachcomber
	14.1 The Theory of Control Charts
	14.2 Control Chart for the Proportion: The p Chart
	14.3 The Red Bead Experiment: Understanding Process Variability
	14.4 Control Chart for an Area of Opportunity: The c Chart
	14.5 Control Charts for the Range and the Mean
		The R Chart
		The X—Chart
	14.6 Process Capability
		Customer Satisfaction and Specification Limits
		Capability Indices
		CPL, CPU, and Cpk
	14.7 Total Quality Management
	14.8 Six Sigma
		The DMAIC Model
		Roles in a Six Sigma Organization
		Lean Six Sigma
	Using Statistics: Finding Quality at the Beachcomber, Revisited
	Summary
	References
	Key Equations
	Key Terms
	Chapter Review Problems
	The Harnswell Sewing Machine Company Case
	Managing Ashland Multicomm Services
	Chapter 14 Excel Guide
		EG14.1 The Theory of Control Charts
		EG14.2 Control Chart for the Proportion: The p Chart
		EG14.3 The Red Bead Experiment: Understanding Process Variability
		EG14.4 Control Chart for an Area of Opportunity: The c Chart
		EG14.5 Control Charts for the Range and the Mean
		EG14.6 Process Capability
	Chapter 14 Minitab Guide
		MG14.1 The Theory of Control Charts
		MG14.2 Control Chart for the Proportion: the p Chart
		MG14.3 The Red Bead Experiment: Understanding Process Variability
		MG14.4 Control Chart for an Area of Opportunity: the c Chart
		MG14.5 Control Charts for the Range and the Mean
		MG14.6 Process Capability
Appendices
	Appendix A: Basic Math Concepts and Symbols
		A.1 Rules for Arithmetic Operations
		A.2 Rules for Algebra: Exponents and Square Roots
		A.3 Rules for Logarithms
		A.4 Summation Notation
		A.5 Statistical Symbols
		A.6 Greek Alphabet
	Appendix B: Important Excel and Minitab Skills
		B.1 Basic Excel Operations
		B.2 Formulas and Cell References
		B.3 Entering Formulas into Worksheets
		B.4 Pasting with Paste Special
		B.5 Basic Worksheet Cell Formatting
		B.6 Chart Formatting
		B.7 Selecting Cell Ranges for Charts
		B.8 Deleting the “Extra” Histogram Bar
		B.9 Creating Histograms for Discrete Probability Distributions
		B.10 Basic Minitab Operations
	Appendix C: Online Resources
		C.1 About the Online Resources for This Book
		C.2 Accessing the Online Resources
		C.3 Details of Downloadable Files
		C.4 PHStat
	Appendix D: Configuring Microsoft Excel
		D.1 Getting Microsoft Excel Ready for Use (ALL)
		D.2 Getting PHStat Ready for Use (ALL)
		D.3 Configuring Excel Security for Add-In Usage (WIN)
		D.4 Opening PHStat (ALL)
		D.5 Using a Visual Explorations Add-In Workbook (ALL)
		D.6 Checking for the Presence of the Analysis ToolPak (ALL)
	Appendix E: Tables
		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 Critical Values of the Studentized Range, Q
		E.7 Critical Values, dL and dU, of the Durbin-Watson Statistic, D (Critical Values Are One-Sided)
		E.8 Control Chart Factors
		E.9 The Standardized Normal Distribution
	Appendix F: Useful Excel Knowledge
		F.1 Useful Keyboard Shortcuts
		F.2 Verifying Formulas and Worksheets
		F.3 New Function Names
		F.4 Understanding the Nonstatistical Functions
	Appendix G: Software FAQs
		G.1 PHStat FAQs
		G.2 Microsoft Excel FAQs
		G.3 FAQs for New Users of Microsoft Excel 2013
		G.4 Minitab FAQs
Self-Test Solutions and Answers to Selected Even-Numbered Problems
Index