Basic Statistics in Business and Economics (ISE HED IRWIN STATISTICS)

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The McGraw Hill Series in Operations and Decision Sciences
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Enhancements to Basic Statistics for Business & Economics, 10e
Brief Contents
Contents
Basic Statistics for Business & Economics
	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
		Practice Test
	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
		Practice Test
	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
		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
		Ethics and Reporting Results
		Chapter Summary
		Chapter Exercises
		Data Analytics
		Practice Test
	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
		Chapter Exercises
		Data Analytics
		Practice Test
	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
		Principles of Counting
			The Multiplication Formula
			The Permutation Formula
			The Combination Formula
			Exercises
		Chapter Summary
		Chapter Exercises
		Data Analytics
		Practice Test
	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
		Poisson Probability Distribution
			Exercises
		Chapter Summary
		Chapter Exercises
		Data Analytics
		Practice Test
	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
		Chapter Summary
		Chapter Exercises
		Data Analytics
		Practice Test
	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
		Chapter Exercises
		Data Analytics
		Practice Test
	9 Estimation and Confidence Intervals
		Introduction
		Point Estimate for a Population Mean
		Confidence Intervals for a Population Mean
			Population Standard Deviation, Known σ
			A Computer Simulation
			Exercises
			Population Standard Deviation, σ 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
		Chapter Summary
		Chapter Exercises
		Data Analytics
		Practice Test
	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
		Chapter Summary
		Chapter Exercises
		Data Analytics
		Practice Test
	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
		Chapter Exercises
		Data Analytics
		Practice Test
	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
		Chapter Summary
		Chapter Exercises
		Data Analytics
		Practice Test
	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
		Chapter Exercises
		Data Analytics
		Practice Test
	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 ŷ Values
			Distribution of Residuals
			Multicollinearity
			Independent Observations
		Qualitative Independent Variables
		Stepwise Regression
			Exercises
		Review of Multiple Regression
		Chapter Summary
		Chapter Exercises
		Data Analytics
		Practice Test
	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
		Contingency Table Analysis
			Exercises
		Chapter Summary
		Chapter Exercises
		Data Analytics
		Practice Test
	Appendixes
		Appendix A: Data Sets
		Appendix B: Tables
		Appendix C: Answers to Odd-Numbered Chapter Exercises & Solutions to Practice Test
		Appendix D: Answers to Self-Review
	Glossary
	Index
	Key Formula
	Areas under the Normal Curve