ISE Statistical Techniques in Business and Economics (ISE HED IRWIN STATISTICS)

Cover
Statistical Techniques in Business & Economics
Dedication
A Note from the Authors
Additional Resources
Acknowledgments
Brief Contents
Contents
Chapter 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
Chapter 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
Chapter 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
Chapter 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
Chapter 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
Chapter 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
Chapter 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
Chapter 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
Chapter 9: Estimation and Confidence Intervals
	Introduction
	Point Estimate for a Population Mean
	Confidence Intervals for a Population Mean
		Population Standard Deviation, Known
		A Computer Simulation
	Exercises
		Population Standard Deviation, 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
Chapter 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
Chapter 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
Chapter 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
Chapter 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
Chapter 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 y 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
Chapter 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
Chapter 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
Chapter 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
Chapter 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
Chapter 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
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