Essentials of Modern Business Statistics with Microsoft Excel

Title Page
Copyright
Brief Contents
Contents
Preface
Acknowledgments
Chapter 1: Data and Statistics
	Statistics In Practice: Bloomberg Businessweek
	1.1 Applications in Business and Economics
		Accounting
		Finance
		Marketing
		Production
		Economics
		Information Systems
	1.2 Data
		Elements, Variables, and Observations
		Scales of Measurement
		Categorical and Quantitative Data
		Cross-Sectional and Time Series Data
	1.3 Data Sources
		Existing Sources
		Observational Study
		Experiment
		Time and Cost Issues
		Data Acquisition Errors
	1.4 Descriptive Statistics
	1.5 Statistical Inference
	1.6 Statistical Analysis Using Microsoft Excel
		Data Sets and Excel Worksheets
		Using Excel for Statistical Analysis
	1.7 Analytics
	1.8 Big Data and Data Mining
	1.9 Ethical Guidelines for Statistical Practice
	Summary
	Glossary
	Supplementary Exercises
Chapter 2: Descriptive Statistics: Tabular and Graphical Displays
	Statistics In Practice: Colgate-Palmolive Company
	2.1 Summarizing Data for a Categorical Variable
		Frequency Distribution
		Relative Frequency and Percent Frequency Distributions
		Using Excel to Construct a Frequency Distribution, a Relative Frequency Distribution, and a Percent Frequency Distribution
		Bar Charts and Pie Charts
		Using Excel to Construct a Bar Chart and a Pie Chart
	2.2 Summarizing Data for a Quantitative Variable
		Frequency Distribution
		Relative Frequency and Percent Frequency Distributions
		Using Excel to Construct a Frequency Distribution
		Dot Plot
		Histogram
		Using Excel’s Recommended Charts Tool to Construct a Histogram
		Cumulative Distributions
		Stem-and-Leaf Display
	2.3 Summarizing Data for Two Variables Using Tables
		Crosstabulation
		Using Excel’s PivotTable Tool to Construct a Crosstabulation
		Simpson’s Paradox
	2.4 Summarizing Data for Two Variables Using Graphical Displays
		Scatter Diagram and Trendline
		Using Excel to Construct a Scatter Diagram and a Trendline
		Side-by-Side and Stacked Bar Charts
		Using Excel’s Recommended Charts Tool to Construct Side-by-Side and Stacked Bar Charts
	2.5 Data Visualization: Best Practices in Creating Effective Graphical Displays
		Creating Effective Graphical Displays
		Choosing the Type of Graphical Display
		Data Dashboards
		Data Visualization in Practice: Cincinnati Zoo and Botanical Garden
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Pelican Stores
	Case Problem 2: Motion Picture Industry
	Case Problem 3: Queen City
	Case Problem 4: Cut-Rate Machining, Inc.
Chapter 3: Descriptive Statistics: Numerical Measures
	Statistics In Practice: Small Fry Design
	3.1 Measures of Location
		Mean
		Median
		Mode
		Using Excel to Compute the Mean, Median, and Mode
		Weighted Mean
		Geometric Mean
		Using Excel to Compute the Geometric Mean
		Percentiles
		Quartiles
		Using Excel to Compute Percentiles and Quartiles
	3.2 Measures of Variability
		Range
		Interquartile Range
		Variance
		Standard Deviation
		Using Excel to Compute the Sample Variance and Sample Standard Deviation
		Coefficient of Variation
		Using Excel’s Descriptive Statistics Tool
	3.3 Measures of Distribution Shape, Relative Location, and Detecting Outliers
		Distribution Shape
		z-Scores
		Chebyshev’s Theorem
		Empirical Rule
		Detecting Outliers
	3.4 Five-Number Summaries and Box Plots
		Five-Number Summary
		Box Plot
		Using Excel to Construct a Box Plot
		Comparative Analysis Using Box Plots
		Using Excel to Construct a Comparative Analysis Using Box Plots
	3.5 Measures of Association Between Two Variables
		Covariance
		Interpretation of the Covariance
		Correlation Coefficient
		Interpretation of the Correlation Coefficient
		Using Excel to Compute the Sample Covariance and Sample Correlation Coefficient
	3.6 Data Dashboards: Adding Numerical Measures to Improve Effectiveness
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Pelican Stores
	Case Problem 2: Motion Picture Industry
	Case Problem 3: Business Schools of Asia-Pacific
	Case Problem 4: Heavenly Chocolates Website Transactions
	Case Problem 5: African Elephant Populations
Chapter 4: Introduction to Probability
	Statistics In Practice: National Aeronautics And Space Administration
	4.1 Experiments, Counting Rules, and Assigning Probabilities
		Counting Rules, Combinations, and Permutations
		Assigning Probabilities
		Probabilities for the KP&L Project
	4.2 Events and Their Probabilities
	4.3 Some Basic Relationships of Probability
		Complement of an Event
		Addition Law
	4.4 Conditional Probability
		Independent Events
		Multiplication Law
	4.5 Bayes’ Theorem
		Tabular Approach
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Hamilton County Judges
	Case Problem 2: Rob’s Market
Chapter 5: Discrete Probability Distributions
	Statistics In Practice: Citibank
	5.1 Random Variables
		Discrete Random Variables
		Continuous Random Variables
	5.2 Developing Discrete Probability Distributions
	5.3 Expected Value and Variance
		Expected Value
		Variance
		Using Excel to Compute the Expected Value, Variance, and Standard Deviation
	5.4 Bivariate Distributions, Covariance, and Financial Portfolios
		A Bivariate Empirical Discrete Probability Distribution
		Financial Applications
		Summary
	5.5 Binomial Probability Distribution
		A Binomial Experiment
		Martin Clothing Store Problem
		Using Excel to Compute Binomial Probabilities
		Expected Value and Variance for the Binomial Distribution
	5.6 Poisson Probability Distribution
		An Example Involving Time Intervals
		An Example Involving Length or Distance Intervals
		Using Excel to Compute Poisson Probabilities
	5.7 Hypergeometric Probability Distribution
		Using Excel to Compute Hypergeometric Probabilities
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Go Bananas!
	Case Problem 2: McNeil’s Auto Mall
	Case Problem 3: Grievance Committee at Tuglar Corporation
	Case Problem 4: Sagittarius Casino
Chapter 6: Continuous Probability Distributions
	Statistics In Practice: Procter & Gamble
	6.1 Uniform Probability Distribution
		Area as a Measure of Probability
	6.2 Normal Probability Distribution
		Normal Curve
		Standard Normal Probability Distribution
		Computing Probabilities for Any Normal Probability Distribution
		Grear Tire Company Problem
		Using Excel to Compute Normal Probabilities
	6.3 Exponential Probability Distribution
		Computing Probabilities for the Exponential Distribution
		Relationship Between the Poisson and Exponential Distributions
		Using Excel to Compute Exponential Probabilities
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Specialty Toys
	Case Problem 2: Gebhardt Electronics
Chapter 7: Sampling and Sampling Distributions
	Statistics In Practice: Meadwestvaco Corporation
	7.1 The Electronics Associates Sampling Problem
	7.2 Selecting a Sample
		Sampling from a Finite Population
		Sampling from an Infinite Population
	7.3 Point Estimation
		Practical Advice
	7.4 Introduction to Sampling Distributions
	7.5 Sampling Distribution of x_(Bar)
		Expected Value of x_(Bar)
		Standard Deviation of x_(Bar)
		Form of the Sampling Distribution of x_(Bar)
		Sampling Distribution of x_(Bar) for the EAI Problem
		Practical Value of the Sampling Distribution of x_(Bar)
		Relationship Between the Sample Size and the Sampling Distribution of x_(Bar)
	7.6 Sampling Distribution of p_(Bar)
		Expected Value of p_(Bar)
		Standard Deviation of p_(Bar)
		Form of the Sampling Distribution of p_(Bar)
		Practical Value of the Sampling Distribution of p_(Bar)
	7.7 Other Sampling Methods
		Stratified Random Sampling
		Cluster Sampling
		Systematic Sampling
		Convenience Sampling
		Judgment Sampling
	7.8 Practical Advice: Big Data and Errors in Sampling
		Sampling Error
		Nonsampling Error
		Implications of Big Data
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Marion Dairies
Chapter 8: Interval Estimation
	Statistics In Practice: Food Lion
	8.1 Population Mean: sigma Known
		Margin of Error and the Interval Estimate
		Using Excel
		Practical Advice
	8.2 Population Mean: sigma Unknown
		Margin of Error and the Interval Estimate
		Using Excel
		Practical Advice
		Using a Small Sample
		Summary of Interval Estimation Procedures
	8.3 Determining the Sample Size
	8.4 Population Proportion
		Using Excel
		Determining the Sample Size
	8.5 Practical Advice: Big Data and Interval Estimation
		Big Data and the Precision of Confidence Intervals
		Implications of Big Data
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Young Professional Magazine
	Case Problem 2: Gulf Real Estate Properties
	Case Problem 3: Metropolitan Research, Inc.
Chapter 9: Hypothesis Tests
	Statistics In Practice: John Morrell & Company
	9.1 Developing Null and Alternative Hypotheses
		The Alternative Hypothesis as a Research Hypothesis
		The Null Hypothesis as an Assumption to Be Challenged
		Summary of Forms for Null and Alternative Hypotheses
	9.2 Type I and Type II Errors
	9.3 Population Mean: sigma Known
		One-Tailed Test
		Two-Tailed Test
		Using Excel
		Summary and Practical Advice
		Relationship Between Interval Estimation and Hypothesis Testing
	9.4 Population Mean: sigma Unknown
		One-Tailed Test
		Two-Tailed Test
		Using Excel
		Summary and Practical Advice
	9.5 Population Proportion
		Using Excel
		Summary
	9.6 Practical Advice: Big Data and Hypothesis Testing
		Big Data and p-Values
		Implications of Big Data
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Quality Associates, Inc.
	Case Problem 2: Ethical Behavior of Business Students at Bayview University
Chapter 10: Inference About Means and Proportions with Two Populations
	Statistics In Practice: U.S. Food And Drug Administration
	10.1 Inferences About the Difference Between Two Population Means: sigma(subscript_1) and sigma(subscript_2) Known
		Interval Estimation of mu(subscript_1) - mu(subscript_2)
		Using Excel to Construct a Confidence Interval
		Hypothesis Tests About mu(subscript_1) - mu(subscript_2)
		Using Excel to Conduct a Hypothesis Test
		Practical Advice
	10.2 Inferences About the Difference Between Two Population Means: sigma(subscript_1) and sigma(subscript_2) Unknown
		Interval Estimation of mu(subscript_1) - mu(subscript_2)
		Using Excel to Construct a Confidence Interval
		Hypothesis Tests About mu(subscript_1) - mu(subscript_2)
		Using Excel to Conduct a Hypothesis Test
		Practical Advice
	10.3 Inferences About the Difference Between Two Population Means: Matched Samples
		Using Excel to Conduct a Hypothesis Test
	10.4 Inferences About the Difference Between Two Population Proportions
		Interval Estimation of p(subscript_1) - (subscript_2)
		Using Excel to Construct a Confidence Interval
		Hypothesis Tests About p(subscript_1) - p(subscript_2)
		Using Excel to Conduct a Hypothesis Test
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem: Par, Inc.
Chapter 11: Inferences About Population Variances
	Statistics In Practice: U.S. Government Accountability Office
	11.1 Inferences About a Population Variance
		Interval Estimation
		Using Excel to Construct a Confidence Interval
		Hypothesis Testing
		Using Excel to Conduct a Hypothesis Test
	11.2 Inferences About Two Population Variances
		Using Excel to Conduct a Hypothesis Test
	Summary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Air Force Training Program
	Case Problem 2: Meticulous Drill & Reamer
Chapter 12: Tests of Goodness of Fit, Independence, and Multiple Proportions
	Statistics In Practice: United Way
	12.1 Goodness of Fit Test
		Multinomial Probability Distribution
		Using Excel to Conduct a Goodness of Fit Test
	12.2 Test of Independence
		Using Excel to Conduct a Test of Independence
	12.3 Testing for Equality of Three or More Population Proportions
		A Multiple Comparison Procedure
		Using Excel to Conduct a Test of Multiple Proportions
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: A Bipartisan Agenda for Change
	Case Problem 2: Fuentes Salty Snacks, Inc.
	Case Problem 3: Fresno Board Games
Chapter 13: Experimental Design and Analysis of Variance
	Statistics In Practice: Burke Marketing Services, Inc.
	13.1 An Introduction to Experimental Design and Analysis of Variance
		Data Collection
		Assumptions for Analysis of Variance
		Analysis of Variance: A Conceptual Overview
	13.2 Analysis of Variance and the Completely Randomized Design
		Between-Treatments Estimate of Population Variance
		Within-Treatments Estimate of Population Variance
		Comparing the Variance Estimates: The F Test
		ANOVA Table
		Using Excel
		Testing for the Equality of k Population Means: An Observational Study
	13.3 Multiple Comparison Procedures
		Fisher’s LSD
		Type I Error Rates
	13.4 Randomized Block Design
		Air Traffic Controller Stress Test
		ANOVA Procedure
		Computations and Conclusions
		Using Excel
	13.5 Factorial Experiment
		ANOVA Procedure
		Computations and Conclusions
		Using Excel
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Wentworth Medical Center
	Case Problem 2: Compensation for Sales Professionals
	Case Problem 3: TourisTopia Travel
Chapter 14: Simple Linear Regression
	Statistics In Practice: Alliance Data Systems
	14.1 Simple Linear Regression Model
		Regression Model and Regression Equation
		Estimated Regression Equation
	14.2 Least Squares Method
		Using Excel to Construct a Scatter Diagram, Display the Estimated Regression Line, and Display the Estimated Regression Equation
	14.3 Coefficient of Determination
		Using Excel to Compute the Coefficient of Determination
		Correlation Coefficient
	14.4 Model Assumptions
	14.5 Testing for Significance
		Estimate of sigma(superscript2)
		t Test
		Confidence Interval for Bita(subscript1)
		F Test
		Some Cautions About the Interpretation of Significance Tests
	14.6 Using the Estimated Regression Equation for Estimation and Prediction
		Interval Estimation
		Confidence Interval for the Mean Value of y
		Prediction Interval for an Individual Value of y
	14.7 Excel’s Regression Tool
		Using Excel’s Regression Tool for the Armand’s Pizza Parlors Example
		Interpretation of Estimated Regression Equation Output
		Interpretation of ANOVA Output
		Interpretation of Regression Statistics Output
	14.8 Residual Analysis: Validating Model Assumptions
		Residual Plot Against x
		Residual Plot Against y(Bar)
		Standardized Residuals
		Using Excel to Construct a Residual Plot
		Normal Probability Plot
	14.9 Outliers and Influential Observations
		Detecting Outliers
		Detecting Influential Observations
	14.10 Practical Advice: Big Data and Hypothesis Testing in Simple Linear Regression
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Measuring Stock Market Risk
	Case Problem 2: U.S. Department of Transportation
	Case Problem 3: Selecting a Point-and-Shoot Digital Camera
	Case Problem 4: Finding the Best Car Value
	Case Problem 5: Buckeye Creek Amusement Park
	Appendix 14.1: Calculus-Based Derivation of Least Squares Formulas
	Appendix 14.2: A Test for Significance Using Correlation
Chapter 15: Multiple Regression
	Statistics In Practice: International Paper
	15.1 Multiple Regression Model
		Regression Model and Regression Equation
		Estimated Multiple Regression Equation
	15.2 Least Squares Method
		An Example: Butler Trucking Company
		Using Excel’s Regression Tool to Develop the Estimated Multiple Regression Equation
		Note on Interpretation of Coefficients
	15.3 Multiple Coefficient of Determination
	15.4 Model Assumptions
	15.5 Testing for Significance
		F Test
		t Test
		Multicollinearity
	15.6 Using the Estimated Regression Equation for Estimation and Prediction
	15.7 Categorical Independent Variables
		An Example: Johnson Filtration, Inc.
		Interpreting the Parameters
		More Complex Categorical Variables
	15.8 Residual Analysis
		Residual Plot Against y⁄
		Standardized Residual Plot Against y⁄
	Practical Advice: Big Data And Hypothesis Testing In Multiple Regression
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Consumer Research, Inc.
	Case Problem 2: Predicting Winnings for NASCAR Drivers
	Case Problem 3: Finding the Best Car Value
Appendix A: References and Bibliography
Appendix B: Tables
Appendix C: Summation Notation
Appendix D: Self-Test Solutions and Answers to Even-Numbered Exercises (online)
Appendix E: Microsoft Excel 2016 and Tools for Statistical Analysis
Index