Essentials of Business Statistics

Cover
Essentials of Business Statistics
Dedication
ABOUT THE AUTHORS
ACKNOWLEDGMENTS
BRIEF CONTENTS
CONTENTS
Chapter 1: Statistics and Data
	1.1 The Relevance of Statistics
	1.2 What is Statistics?
		The Need for Sampling
		Cross-Sectional and Time Series Data
		Structured and Unstructured Data
		Big Data
		Data on the Web
	1.3 Variables and Scales of Measurement
		The Nominal Scale
		The Ordinal Scale
		The Interval Scale
		The Ratio Scale
		Synopsis of Introductory Case
	Conceptual Review
Chapter 2: Tabular and Graphical Methods
	2.1 Summarizing Qualitative Data
		Pie Charts and Bar Charts
		Cautionary Comments When Constructing or Interpreting Charts or Graphs
		Using Excel to Construct a Pie Chart and a Bar Chart
			A Pie Chart
			A Bar Chart
	2.2 Summarizing Quantitative Data
		Guidelines for Constructing a Frequency Distribution
		Synopsis Of Introductory Case
		Histograms, Polygons, and Ogives
		Using Excel to Construct a Histogram, a Polygon, and an Ogive
			A Histogram Constructed from Raw Data
			A Histogram Constructed from a Frequency Distribution
			A Polygon
			An Ogive
	2.3 Stem-and-Leaf Diagrams
	2.4 Scatterplots
		Using Excel to Construct a Scatterplot
		Writing with Statistics
		Conceptual Review
	Additional Exercises And Case Studies
		Exercises
		Case Studies
	Appendix 2.1 Guidelines for Other Software Packages
Chapter 3: Numerical Descriptive Measures
	3.1 Measures of Central Location
		The Mean
		The Median
		The Mode
			The Weighted Mean
		Using Excel to Calculate Measures of Central Location
			Using Excel’s Function Option
			Using Excel’s Data Analysis Toolpak Option
			Note on Symmetry
	3.2 Percentiles and Boxplots
		Calculating the pth Percentile
			Note on Calculating Percentiles
		Constructing and Interpreting a Boxplot
	3.3 Measures of Dispersion
		Range
		The Mean Absolute Deviation
		The Variance and the Standard Deviation
		The Coefficient of Variation
		Using Excel to Calculate Measures of Dispersion
			Using Excel’s Function Option
			Using Excel’s Data Analysis Toolpak Option
	3.4 Mean-Variance Analysis and the Sharpe Ratio
		Synopsis of Introductory Case
	3.5 Analysis of Relative Location
		Chebyshev’s Theorem
		The Empirical Rule
		z-Scores
	3.6 Summarizing Grouped Data
	3.7 Measures of Association
		Using Excel to Calculate Measures of Association
		Writing with Statistics
		Conceptual Review
	Additional Exercises and Case Studies
		Exercises
		Case Studies
	Appendix 3.1: Guidelines for Other Software Packages
Chapter 4: Introduction to Probability
	4.1 Fundamental Probability Concepts
		Events
		Assigning Probabilities
	4.2 Rules of Probability
		The Complement Rule
		The Addition Rule
			The Addition Rule for Mutually Exclusive Events
		Conditional Probability
		Independent and Dependent Events
		The Multiplication Rule
			The Multiplication Rule for Independent Events
	4.3 Contingency Tables and Probabilities
		A Note on Independence
		Synopsis of Introductory Case
	4.4 The Total Probability Rule and Bayes’ Theorem
		The Total Probability Rule
		Bayes’ Theorem
		Writing With Statistics
		Conceptual Review
	Additional Exercises and Case Studies
		Exercises
		Case Studies
Chapter 5: Discrete Probability Distributions
	5.1 Random Variables and Discrete Probability Distributions
		The Discrete Probability Distribution
	5.2 Expected Value, Variance, and Standard Deviation
		Expected Value
		Variance and Standard Deviation
		Risk Neutrality and Risk Aversion
	5.3 The Binomial Distribution
		Using Excel to Obtain Binomial Probabilities
	5.4 The Poisson Distribution
		Synopsis of Introductory Case
		Using Excel to Obtain Poisson Probabilities
	5.5 The Hypergeometric Distribution
		Using Excel to Obtain Hypergeometric Probabilities
		Writing with Statistics
		Conceptual Review
	Additional Exercises and Case Studies
		Exercises
		Case Studies
	Appendix 5.1: Guidelines for Other Software Packages
Chapter 6: Continuous Probability Distributions
	6.1 Continuous Random Variables and the Uniform Distribution
		The Continuous Uniform Distribution
	6.2 The Normal Distribution
		Characteristics of the Normal Distribution
		The Standard Normal Distribution
		Finding a Probability for a Given z Value
		Finding a z Value for a Given Probability
		The Transformation of Normal Random Variables
		Synopsis of Introductory Case
		A Note on the Normal Approximation of the Binomial Distribution
		Using Excel for the Normal Distribution
	6.3 The Exponential Distribution
		Using Excel for the Exponential Distribution
		Writing with Statistics
		Conceptual Review
	Additional Exercises and Case Studies
		Exercises
		Case Studies
	Appendix 6.1: Guidelines for Other Software Packages
Chapter 7: Sampling and Sampling Distributions
	7.1 Sampling
		Classic Case of a “Bad” Sample: The Literary Digest Debacle of 1936
		Trump’s Stunning Victory in 2016
		Sampling Methods
		Using Excel to Generate a Simple Random Sample
	7.2 The Sampling Distribution of the Sample Mean
		The Expected Value and the Standard Error of the Sample Mean
		Sampling from a Normal Population
		The Central Limit Theorem
	7.3 The Sampling Distribution of the Sample Proportion
		The Expected Value and the Standard Error of the Sample Proportion
		Synopsis of Introductory Case
	7.4 The Finite Population Correction Factor
	7.5 Statistical Quality Control
		Control Charts
		Using Excel to Create a Control Chart
		Writing with Statistics
		Conceptual Review
		Additional Exercises and Case Studies
		Exercises
		Case Studies
	Appendix 7.1: Derivation of the Mean and the Variance for X and P
	Appendix 7.2: Properties of Point Estimators
	Appendix 7.3: Guidelines for Other Software Packages
Chapter 8: Interval Estimation
	8.1 Confidence Interval for the Population Mean when σ is Known
		Constructing a Confidence Interval for μ When σ Is Known
		The Width of a Confidence Interval
		Using Excel to Construct a Confidence Interval for μ When σ Is Known
	8.2 Confidence Interval for the Population Mean When σ  is Unknown
		The t Distribution
			Summary of the tdf Distribution
			Locating tdf Values and Probabilities
		Constructing a Confidence Interval for   When   Is Unknown
		Using Excel to Construct a Confidence Interval for   When   Is Unknown
	8.3 Confidence Interval for the Population Proportion
	8.4 Selecting the Required Sample Size
		Selecting n to Estimate
		Selecting n to Estimate p
		Synopsis of Introductory Case
		Writing with Statistics
		Conceptual Review
	Additional Exercises and Case Studies
		Exercises
		Case Studies
	Appendix 8.1: Guidelines for Other Software Packages
Chapter 9: Hypothesis Testing
	9.1 Introduction to Hypothesis Testing
		The Decision to “Reject” or “Not Reject” the Null Hypothesis
		Defining the Null and the Alternative Hypotheses
		Type I and Type II Errors
	9.2 Hypothesis Test for the Population Mean When σ is Known
		The p-Value Approach
		Confidence Intervals and Two-Tailed Hypothesis Tests
		Using Excel to Test   When   Is Known
		One Last Remark
	9.3 Hypothesis Test for the Population Mean When σ is Unknown
		Using Excel to Test μ When σ is Unknown
		Synopsis of Introductory Case
	9.4 Hypothesis Test for the Population Proportion
		Writing with Statistics
		Conceptual Review
	Additional Exercises and Case Studies
		Exercises
		Case Studies
	Appendix 9.1: The Critical Value Approach
	Appendix 9.2: Guidelines for Other Software Packages
Chapter 10: Comparisons Involving Means
	10.1 Inference Concerning the Difference Between Two Means
		Confidence Interval for μ1 − μ2
		Hypothesis Test for μ1 − μ2
		Using Excel for Testing Hypotheses about μ1 − μ2
	10.2 Inference Concerning Mean Differences
		Recognizing a Matched-Pairs Experiment
		Confidence Interval for μD
		Hypothesis Test for μD
		Using Excel for Testing Hypotheses about μD
		Synopsis of Introductory Case
	10.3 Inference Concerning Differences Among Many Means
		The F Distribution
			Finding F (df1 ,df2 ) Values and Probabilities
		One-Way ANOVA Test
			Between-Treatments Estimate of σ2: MSTR
			Within-Treatments Estimate of σ2: MSE
			The One-Way ANOVA Table
		Using Excel to Construct a One-Way ANOVA Table
		Writing with Statistics
		Conceptual Review
	Additional Exercises and Case Studies
		Exercises
		Case Studies
	Appendix 10.1: Guidelines for Other Software Packages
Chapter 11: Comparisons Involving Proportions
	11.1 Inference Concerning the Difference Between Two Proportions
		Confidence Interval for p1 − p2
		Hypothesis Test for p1 − p2
	11.2 Goodness-Of-Fit Test for a Multinomial Experiment
		The X2 Distribution
			Finding  χd2f Values and Probabilities
	11.3 Chi-Square Test For Independence
		Synopsis of Introductory Case
		Writing with Statistics
		Conceptual Review
	Additional Exercises and Case Studies
		Exercises
		Case Studies
	Appendix 11.1: Guidelines for Other Software Packages
Chapter 12: Basics of Regression Analysis
	12.1 The Simple Linear Regression Model
		Determining the Sample Regression Equation
		Using Excel
			Constructing a Scatterplot with Trendline
			Estimating a Simple Linear Regression Model
	12.2 The Multiple Linear Regression Model
		Using Excel to Estimate a Multiple Linear Regression Model
	12.3 Goodness-of-Fit Measures
		The Standard Error of the Estimate
		The Coefficient of Determination, R2
		The Adjusted R2
	12.4 Tests of Significance
		Tests of Individual Significance
			A Test for a Nonzero Slope Coefficient
		Test of Joint Significance
		Reporting Regression Results
		Synopsis of Introductory Case
	12.5 Model Assumptions and Common Violations
		Common Violation 1: Nonlinear Patterns
			Detection
			Remedy
		Common Violation 2: Multicollinearity
			Detection
			Remedy
		Common Violation 3: Changing Variability
			Detection
			Remedy
		Common Violation 4: Correlated Observations
			Detection
			Remedy
		Common Violation 5: Excluded Variables
			Remedy
		Summary
		Using Excel to Construct Residual Plots
		Writing with Statistics
		Conceptual Review
	Additional Exercises and Case Studies
		Case Studies
	Appendix 12.1: Guidelines for Other Software Packages
Chapter 13: More on Regression Analysis
	13.1 Dummy Variables
		A Qualitative Explanatory Variable with Two Categories
		A Qualitative Explanatory Variable with Multiple Categories
	13.2 Interactions with Dummy Variables
		Synopsis of Introductory Case
	13.3 Regression Models for Nonlinear Relationships
		Quadratic Regression Models
		Regression Models with Logarithms
			The Log-Log Model
			The Logarithmic Model
			The Exponential Model
	13.4 Trend Forecasting Models
		The Linear and the Exponential Trend
		Polynomial Trends
	13.5 Forecasting with Trend and Seasonality
		Seasonal Dummy Variables
		Writing with Statistics
		Conceptual Review
	Additional Exercises and Case Studies
		Case Studies
Appendixes
	Appendix A Tables
	Appendix B Answers to Selected Even-Numbered Exercises
Glossary
INDEX