Complete business statistics

Title
Contents
1 Introduction and Descriptive Statistics
	1–1 Using Statistics
		Samples and Populations
			Data and Data Collection
	1–2 Percentiles and Quartiles
	1–3 Measures of Central Tendency
	1–4 Measures of Variability
	1–5 Grouped Data and the Histogram
	1–6 Skewness and Kurtosis
	1–7 Relations between the Mean and the Standard Deviation
		Chebyshev’s Theorem
		The Empirical Rule
	1–8 Methods of Displaying Data
		Pie Charts
		Bar Charts
		Frequency Polygons and Ogives
		A Caution about Graphs
		Time Plots
	1–9 Exploratory Data Analysis
		Stem-and-Leaf Displays
		Box Plots
	1–10 Using the Computer
		Using Excel for Descriptive Statistics and Plots
		Using MINITAB for Descriptive Statistics and Plots
	1–11 Summary and Review of Terms
	Case 1: NASDAQ Volatility
2 Probability
	2–1 Using Statistics
		2–2 Basic Definitions: Events, Sample Space, and Probabilities
		2–3 Basic Rules for Probability
			The Range of Values
			The Rule of Complements
			Mutually Exclusive Events
		2–4 Conditional Probability
		2–5 Independence of Events
			Product Rules for Independent Events
		2–6 Combinatorial Concepts
		2–7 The Law of Total Probability and Bayes’ Theorem
			The Law of Total Probability
				Bayes’ Theorem
			Case 2: Job Applications
		2–8 The Joint Probability Table
		2–9 Using the Computer
			Excel Templates and Formulas
			Using MINITAB
		2–10 Summary and Review of Terms
3 Random Variables
	3–1 Using Statistics
		Discrete and Continuous Random Variables
		Cumulative Distribution Function
	3–2 Expected Values of Discrete Random Variables
		The Expected Value of a Function of a Random Variable
		Variance and Standard Deviation of a Random Variable
		Variance of a Linear Function of a Random Variable
	3–3 Sum and Linear Composites of Random Variables
		Chebyshev’s Theorem
		The Templates for Random Variables
	3–4 Bernoulli Random Variable
	3–5 The Binomial Random Variable
		Conditions for a Binomial Random Variable
		Binomial Distribution Formulas
		The Template
		Problem Solving with the Template
	3–6 Negative Binomial Distribution
		Negative Binomial Distribution Formulas
		Problem Solving with the Template
	3–7 The Geometric Distribution
		Geometric Distribution Formulas
		Problem Solving with the Template
	3–8 The Hypergeometric Distribution
		Hypergeometric Distribution Formulas
		Problem Solving with the Template
	3–9 The Poisson Distribution
		Problem Solving with the Template
	3–10 Continuous Random Variables
	3–11 The Uniform Distribution
		Problem Solving with the Template
	3–12 The Exponential Distribution
		A Remarkable Property
		3–14 Summary and Review of Terms
		The Template
		Value at Risk
	3–13 Using the Computer
		Using Excel Formulas for Some Standard Distributions
		Using MINITAB for Some Standard Distributions
	Case 3: Concepts Testing
4 The Normal Distribution
	4–1 Using Statistics
	4–2 Properties of the Normal Distribution
	4–3 The Standard Normal Distribution
		Finding Probabilities of the Standard Normal Distribution
		Finding Values of Z Given a Probability
	4–4 The Transformation of Normal Random Variables
		Using the Normal Transformation
	4–5 The Inverse Transformation
	4–6 The Template
		Problem Solving with the Template
	4–7 Normal Approximation of Binomial Distributions
	4–8 Using the Computer
		Using Excel Functions for a Normal Distribution
		Using MINITAB for a Normal Distribution
	4–9 Summary and Review of Terms
	Case 4: Acceptable Pins
	Case 5: Multicurrency Decision
5 Sampling and Sampling Distributions
	5–1 Using Statistics
	5–2 Sample Statistics as Estimators of Population Parameters
		Obtaining a Random Sample
		Other Sampling Methods
		Nonresponse
	5–3 Sampling Distributions
		The Central Limit Theorem
		The History of the Central Limit Theorem
		The Standardized Sampling Distribution of the Sample Mean When � Is Not Known
		The Sampling Distribution of the Sample Proportion ˆ P
	5–4 Estimators and Their Properties
		Applying the Concepts of Unbiasedness, Efficiency, Consistency, and Sufficiency
	5–5 Degrees of Freedom
		5–6 Using the Computer
			Using Excel for Generating Sampling Distributions
				Using MINITAB for Generating Sampling Distributions
				5–7 Summary and Review of Terms
				Case 6: Acceptance Sampling of Pins
	Case 9: Tiresome Tires I
6 Confidence Intervals
	6–1 Using Statistics
	6–2 Confidence Interval for the Population Mean When the Population Standard Deviation Is Known
		The Template
	6–3 Confidence Intervals for � When � Is Unknown— The t Distribution
		The t Distribution
	6–4 Large-Sample Confidence Intervals for the Population Proportion p
		The Template
	6–5 Confidence Intervals for the Population Variance
		The Template
	6–6 Sample-Size Determination
	6–7 The Templates
		Optimizing Population Mean Estimates
		Determining the Optimal Half-Width
		Using the Solver
		Optimizing Population Proportion Estimates
	6–8 Using the Computer
		Using Excel Built-In Functions for Confidence Interval Estimation
		Using MINITAB for Confidence Interval Estimation
	6–9 Summary and Review of Terms
	Case 7: Presidential Polling
	Case 8: Privacy Problem
7 Hypothesis Testing
	7–1 Using Statistics
		The Null Hypothesis
	7–2 The Concepts of Hypothesis Testing
		Evidence Gathering
		Type I and Type II Errors
		The p-Value
		The Significance Level
		Optimal � and the Compromise between Type I and Type II Errors
		� and Power
		Sample Size
	7–3 Computing the p-Value
		The Test Statistic
		p-Value Calculations
		One-Tailed and Two-Tailed Tests
		Computing �
	7–4 The Hypothesis Test
		Testing Population Means
		A Note on t Tables and p-Values
		The Templates
		Testing Population Proportions
		Testing Population Variances
	7–5 Pretest Decisions
		Testing Population Means
		Manual Calculation of Required Sample Size
		Testing Population Proportions
		Manual Calculation of Sample Size
	7–6 Using the Computer
		Using Excel for One-Sample Hypothesis Testing
		Using MINITAB for One-Sample Hypothesis Testing
	7–7 Summary and Review of Terms
8 The Comparison of Two Populations
	8–1 Using Statistics
	8–2 Paired-Observation Comparisons
		The Template
		Confidence Intervals
		The Template
	8–3 A Test for the Difference between Two Population Means Using Independent Random Samples
		The Templates
		Confidence Intervals
		The Templates
		Confidence Intervals
	8–4 A Large-Sample Test for the Difference between Two Population Proportions
		Confidence Intervals
		The Template
	8–5 The F Distribution and a Test for Equality of Two Population Variances
		A Statistical Test for Equality of Two Population Variances
		The Templates
	8–6 Using the Computer
		Using Excel for Comparison of Two Populations
		Using MINITAB for Comparison of Two Samples
	8–7 Summary and Review of Terms
	Case 10: Tiresome Tires II
9 Analysis of Variance
	9–1 Using Statistics
	9–2 The Hypothesis Test of Analysis of Variance
		The Test Statistic
	9–3 The Theory and the Computations of ANOVA
		The Sum-of-Squares Principle
		The Degrees of Freedom
		The Mean Squares
		The Expected Values of the Statistics MSTR and MSE under the Null Hypothesis
		The F Statistic
	9–4 The ANOVA Table and Examples
	9–5 Further Analysis
		The Tukey Pairwise-Comparisons Test
		Conducting the Tests
		The Case of Unequal Sample Sizes, and Alternative Procedures
		The Template
	9–6 Models, Factors, and Designs
		One-Factor versus Multifactor Models
		Fixed-Effects versus Random-Effects Models
		Experimental Design
	9–7 Two-Way Analysis of Variance
		The Two-Way ANOVA Model
		The Hypothesis Tests in Two-Way ANOVA
		Sums of Squares, Degrees of Freedom, and Mean Squares
		The F Ratios and the Two-Way ANOVA Table
		The Template
		The Overall Significance Level
		The Tukey Method for Two-Way Analysis
		Extension of ANOVA to Three Factors
		Two-Way ANOVA with One Observation per Cell
	9–8 Blocking Designs
		Randomized Complete Block Design
		The Template
	9–9 Using the Computer
		Using Excel for Analysis of Variance
		Using MINITAB for Analysis of Variance
	9–10 Summary and Review of Terms
	Case 11: Rating Wines
	Case 12: Checking Out Checkout
10 Simple Linear Regression and Correlation
	10–1 Using Statistics
		Model Building
	10–2 The Simple Linear Regression Model
	10–3 Estimation: The Method of Least Squares
		The Template
	10–4 Error Variance and the Standard Errors of Regression Estimators
		Confidence Intervals for the Regression Parameters
	10–5 Correlation
	10–6 Hypothesis Tests about the Regression Relationship
		Other Tests
	10–7 How Good Is the Regression?
	10–8 Analysis-of-Variance Table and an F Test of the Regression Model
	10–9 Residual Analysis and Checking for Model Inadequacies
		A Check for the Equality of Variance of the Errors
		Testing for Missing Variables
		Detecting a Curvilinear Relationship between Y and X
		The Normal Probability Plot
	10–10 Use of the Regression Model for Prediction
		Point Predictions
		Prediction Intervals
		A Confidence Interval for the Average Y, Given a Particular Value of X
	10–11 Using the Computer
		The Excel Solver Method for Regression
		The Excel LINEST Function
		Using MINITAB for Simple Linear Regression Analysis
	10–12 Summary and Review of Terms
	Case 13: Firm Leverage and Shareholder Rights
	Case 14: Risk and Return
11 Multiple Regression
	11–1 Using Statistics
	11–2 The k-Variable Multiple Regression Model
		The Estimated Regression Relationship
	11–3 The F Test of a Multiple Regression Model
	11–4 How Good Is the Regression?
	11–5 Tests of the Significance of Individual Regression Parameters
	11–6 Testing the Validity of the Regression Model
		Residual Plots
		Standardized Residuals
		The Normal Probability Plot
		Outliers and Influential Observations
		Lack of Fit and Other Problems
	11–7 Using the Multiple Regression Model for Prediction
		The Template
		Setting Recalculation to “Manual” on the Template
	11–8 Qualitative Independent Variables
		Interactions between Qualitative and Quantitative Variables
	11–9 Polynomial Regression
		Other Variables and Cross-Product Terms
	11–10 Nonlinear Models and Transformations
		Variance-Stabilizing Transformations
		Regression with Dependent Indicator Variable
	11–11 Multicollinearity
		Causes of Multicollinearity
		Detecting the Existence of Multicollinearity
		Solutions to the Multicollinearity Problem
	11–12 Residual Autocorrelation and the Durbin-Watson Test
	11–13 Partial F Tests and Variable Selection Methods
		Partial F Tests
		Variable Selection Methods
	11–14 Using the Computer
		Multiple Regression Using the Solver
		LINEST Function for Multiple Regression
		Using MINITAB for Multiple Regression
	11–15 Summary and Review of Terms
	Case 15: Return on Capital for Four Different Sectors
12 Time Series, Forecasting, and Index Numbers
	12–1 Using Statistics
	12–2 Trend Analysis
	12–3 Seasonality and Cyclical Behavior
	12–4 The Ratio-to-Moving-Average Method
		The Template
		The Cyclical Component of the Series
		Forecasting a Multiplicative Series
	12–5 Exponential Smoothing Methods
		The Template
	12–6 Index Numbers
		The Consumer Price Index
		The Template
	12–7 Using the Computer
		Using Microsoft Excel in Forecasting and Time Series
		Using MINITAB in Forecasting and Time Series
	12–8 Summary and Review of Terms
	Case 16: Auto Parts Sales Forecast
13 Quality Control and Improvement
	13–1 Using Statistics
	13–2 W. Edwards Deming Instructs
	13–3 Statistics and Quality
		Deming’s 14 Points
		Process Capability
		Control Charts
		Pareto Diagrams
		Six Sigma
		Acceptance Sampling
		Analysis of Variance and Experimental Design
		Taguchi Methods
		The Template
	13–4 The x Chart
		The Template
	13–5 The R Chart and the s Chart
		The R Chart
		The s Chart
	13–6 The p Chart
		The Template
	13–7 The c Chart
		The Template
	13–8 The x Chart
	13–9 Using the Computer
		Using MINITAB for Quality Control
	13–10 Summary and Review of Terms
	Case 17: Quality Control and Improvement at Nashua Corporation
14 Nonparametric Methods and Chi-Square Tests
	14–1 Using Statistics
	14–2 The Sign Test
	14–3 The Runs Test—A Test for Randomness
		Large-Sample Properties
		The Template
		The Wald-Wolfowitz Test
	14–4 The Mann-Whitney U Test
		The Computational Procedure
	14–5 The Wilcoxon Signed-Rank Test
		The Paired-Observations Two-Sample Test
		Large-Sample Version of the Test
		A Test for the Mean or Median of a Single Population
		The Template
	14–6 The Kruskal-Wallis Test—A Nonparametric Alternative to One-Way ANOVA
		The Template
		Further Analysis
	14–7 The Friedman Test for a Randomized Block Design
		The Template
	14–8 The Spearman Rank Correlation Coefficient
		The Template
		14–9 A Chi-Square Test for Goodness of Fit
			A Goodness-of-Fit Test for the Multinomial Distribution
			The Template
			Unequal Probabilities
			The Template
		14–10 Contingency Table Analysis—A Chi-Square Test for Independence
			The Template
		14–11 A Chi-Square Test for Equality of Proportions
			The Median Test
		14–12 Using the Computer
			Using MINITAB for Nonparametric Tests
		14–13 Summary and Review of Terms
		Case 18: The Nine Nations of North America
15 Bayesian Statistics and Decision Analysis
	15–1 Using Statistics
	15–2 Bayes’ Theorem and Discrete Probability Models
		The Template
	15–3 Bayes’ Theorem and Continuous Probability Distributions
		The Normal Probability Model
		Credible Sets
		The Template
	15–4 The Evaluation of Subjective Probabilities
		Assessing a Normal Prior Distribution
	15–5 Decision Analysis: An Overview
		Actions
		Chance Occurrences
		Probabilities
		Final Outcomes
		Additional Information
		Decision
	15–6 Decision Trees
		The Payoff Table
	15–7 Handling Additional Information Using Bayes’ Theorem
		Determining the Payoffs
		Determining the Probabilities
	15–8 Utility
		A Method of Assessing Utility
	15–9 The Value of Information
	15–10 Using the Computer
		The Template
		15–11 Summary and Review of Terms
		Case 19: Pizzas ‘R’ Us
		Case 20: New Drug Development
A References
B Answers to Most Odd-Numbered Problems
C Statistical Tables