Statistics for Business and Economics

by Anderson,David R.

• ISBN13: 9780324200829
• ISBN10: 032420082X
• Edition: CD
• Format: Hardcover
• Copyright: 2004-01-06
• Publisher: Cengage Learning

Summary

This market leading book offers a proven, comprehensive, applications-oriented approach. Written by authors who are highly regarded in the field, the text provides sound methodological development. The discussion and development of each technique is presented in an application setting, with the statistical results providing insights to decisions and solutions to problems.

Table of Contents

Preface	xxi
About the Authors	xxvii
Chapter 1 Data and Statistics	1	(22)
Statistics in Practice: Business Week	2	(1)
1.1 Applications in Business and Economics	3	(2)
Accounting	3	(1)
Finance	3	(1)
Marketing	4	(1)
Production	4	(1)
Economics	4	(1)
1.2 Data	5	(3)
Elements, Variables, and Observations	5	(1)
Scales of Measurement	6	(1)
Qualitative and Quantitative Data	7	(1)
Cross-Sectional and Time Series Data	7	(1)
1.3 Data Sources 8 Existing Sources	8	(4)
Statistical Studies	9	(3)
Data Acquisition Errors	12	(1)
1.4 Descriptive Statistics	12	(2)
1.5 Statistical Inference	14	(2)
1.6 Computers and Statistical Analysis	16	(1)
Summary	16	(1)
Glossary	16	(1)
Exercises	17	(6)
Chapter 2 Descriptive Statistics: Tabular and Graphical Presentations	23	(53)
Statistics in Practice: Colgate-Palmolive Company	24	(1)
2.1 Summarizing Qualitative Data	25	(6)
Frequency Distribution	25	(1)
Relative Frequency and Percent Frequency Distributions	26	(1)
Bar Graphs and Pie Charts	26	(5)
2.2 Summarizing Quantitative Data	31	(9)
Frequency Distribution	31	(1)
Relative Frequency and Percent Frequency Distributions	32	(1)
Dot Plot	32	(1)
Histogram	33	(1)
Cumulative Distributions	34	(2)
Ogive	36	(4)
2.3 Exploratory Data Analysis: The Stein-and-Leaf Display	40	(5)
2.4 Crosstabulations and Scatter Diagrams	45	(9)
Crosstabulation	45	(2)
Simpson's Paradox	47	(2)
Scatter Diagram and Trendline	49	(5)
Summary	54	(2)
Glossary	56	(1)
Key Formulas	57	(1)
Supplementary Exercises	57	(6)
Case Problem Pelican Stores	63	(1)
Appendix 2.1 Using Minitab for Tabular and Graphical Presentations	64	(2)
Appendix 2.2 Using Excel for Tabular and Graphical Presentations	66	(10)
Chapter 3 Descriptive Statistics: Numerical Measures	76	(63)
Statistics in Practice: Small Fry Design	77	(1)
3.1 Measures of Location	78	(9)
Mean	78	(1)
Median	79	(1)
Mode	80	(1)
Percentiles	81	(1)
Quartiles	82	(5)
3.2 Measures of Variability	87	(7)
Range	87	(1)
Interquartile Range	88	(1)
Variance	88	(2)
Standard Deviation	90	(1)
Coefficient of Variation	91	(3)
3.3 Measures of Distribution Shape, Relative Location, and Detecting
Outliers	94	(1)
Distribution Shape	94	(1)
z-Scores	94	(2)
Chebyshev's Theorem	96	(1)
Empirical Rule	97	(1)
Detecting Outliers	98	(3)
3.4 Exploratory Data Analysis	101	(4)
Five-Number Summary	101	(1)
Box Plot	102	(3)
3.5 Measures of Association Between Two Variables	105	(9)
Covariance	106	(1)
Interpretation of the Covariance	107	(3)
Correlation Coefficient	110	(1)
Interpretation of the Correlation Coefficient	111	(3)
3.6 The Weighted Mean and Working with Grouped Data	114	(6)
Weighted Mean	115	(1)
Grouped Data	116	(4)
Summary	120	(1)
Glossary	121	(1)
Key Formulas	122	(2)
Supplementary Exercises	124	(5)
Case Problem 1 Pelican Stores	129	(1)
Case Problem 2 National Health Care Association	130	(1)
Case Problem 3 Business Schools of Asia-Pacific	131	(2)
Appendix 3.1 Descriptive Statistics Using Minitab	133	(2)
Appendix 3.2 Descriptive Statistics Using Excel	135	(4)
Chapter 4 Introduction to Probability	139	(45)
Statistics in Practice: Morton International	140	(1)
4.1 Experiments, Counting Rules, and Assigning Probabilities	141	(10)
Counting Rules, Combinations, and Permutations	142	(4)
Assigning Probabilities	146	(2)
Probabilities for the KP&L Project	148	(3)
4.2 Events and Their Probabilities	151	(4)
4.3 Some Basic Relationships of Probability	155	(6)
Complement of an Event	155	(1)
Addition Law	156	(5)
4.4 Conditional Probability	161	(8)
Independent Events	165	(1)
Multiplication Law	165	(4)
4.5 Bayes' Theorem	169	(6)
Tabular Approach	173	(2)
Summary	175	(1)
Glossary	175	(1)
Key Formulas	176	(1)
Supplementary Exercises	177	(4)
Case Problem Hamilton County Judges	181	(3)
Chapter 5 Discrete Probability Distributions	184	(39)
Statistics in Practice: Citibank	185	(1)
5.1 Random Variables	185	(3)
Discrete Random Variables	186	(1)
Continuous Random Variables	187	(1)
5.2 Discrete Probability Distributions	188	(6)
5.3 Expected Value and Variance	194	(4)
Expected Value	194	(1)
Variance	194	(4)
5.4 Binomial Probability Distribution	198	(10)
A Binomial Experiment	199	(1)
Martin Clothing Store Problem	200	(4)
Using Tables of Binomial Probabilities	204	(1)
Expected Value and Variance for the Binomial Distribution	205	(3)
5.5 Poisson Probability Distribution	208	(4)
An Example Involving Time Intervals	209	(2)
An Example Involving Length or Distance Intervals	211	(1)
5.6 Hypergeometric Probability Distribution	212	(3)
Summary	215	(1)
Glossary	216	(1)
Key Formulas	217	(1)
Supplementary Exercises	218	(2)
Appendix 5.1 Discrete Probability Distributions with Minitab	220	(1)
Appendix 5.2 Discrete Probability Distributions with Excel	221	(2)
Chapter 6 Continuous Probability Distributions	223	(34)
Statistics in Practice: Procter & Gamble	224	(1)
6.1 Uniform Probability Distribution	225	(4)
Area as a Measure of Probability	226	(3)
6.2 Normal Probability Distribution	229	(14)
Normal Curve	229	(2)
Standard Normal Probability Distribution	231	(6)
Computing Probabilities for Any Normal Distribution	237	(1)
Grear Tire Company Problem	238	(5)
6.3 Normal Approximation of Binomial Probabilities	243	(3)
6.4 Exponential Probability Distribution	246	(4)
Computing Probabilities for the Exponential Distribution	246	(2)
Relationship Between the Poisson and Exponential Distributions	248	(2)
Summary	250	(1)
Glossary	250	(1)
Key Formulas	250	(1)
Supplementary Exercises	251	(3)
Case Problem Specialty Toys	254	(1)
Appendix 6.1 Continuous Probability Distributions with Minitab	255	(1)
Appendix 6.2 Continuous Probability Distributions with Excel	256	(1)
Chapter 7 Sampling and Sampling Distributions	257	(40)
Statistics in Practice: MeadWestvaco Corporation	258	(1)
7.1 The Electronics Associates Sampling Problem	259	(1)
7.2 Simple Random Sampling	260	(4)
Sampling from a Finite Population	260	(1)
Sampling from an Infinite Population	261	(3)
7.3 Point Estimation	264	(3)
7.4 Introduction to Sampling Distributions	267	(3)
7.5 Sampling Distribution of x	270	(9)
Expected Value of x	270	(1)
Standard Deviation of x	271	(1)
Form of the Sampling Distribution of x	272	(1)
Sampling Distribution of x for the EAI Problem	273	(1)
Practical Value of the Sampling Distribution of x	274	(1)
Relationship Between the Sample Size and the Sampling Distribution of x	275	(4)
7.6 Sampling Distribution of p	279	(5)
Expected Value of p	280	(1)
Standard Deviation of p	280	(1)
Form of the Sampling Distribution of p	281	(1)
Practical Value of the Sampling Distribution of p	281	(3)
7.7 Properties of Point Estimators	284	(3)
Unbiased	285	(1)
Efficiency	286	(1)
Consistency	287	(1)
7.8 Other Sampling Methods	287	(3)
Stratified Random Sampling	287	(1)
Cluster Sampling	288	(1)
Systematic Sampling	288	(1)
Convenience Sampling	289	(1)
Judgment Sampling	289	(1)
Summary	290	(1)
Glossary	290	(1)
Key Formulas	291	(1)
Supplementary Exercises	292	(2)
Appendix 7.1 The Expected Value and Standard Deviation of x	294	(1)
Appendix 7.2 Random Sampling with Minitab	295	(1)
Appendix 7.3 Random Sampling with Excel	296	(1)
Chapter 8 Interval Estimation	297	(39)
Statistics in Practice: Food Lion	298	(1)
8.1 Population Mean: σ Known	299	(6)
Margin of Error and the Interval Estimate	300	(3)
Practical Advice	303	(2)
8.2 Population Mean: σ Unknown	305	(9)
Margin of Error and the Interval Estimate	306	(3)
Practical Advice	309	(1)
Using a Small Sample	309	(2)
Summary of Interval Estimation Procedures	311	(3)
8.3 Determining the Sample Size	314	(3)
8.4 Population Proportion	317	(5)
Determining the Sample Size	319	(3)
Summary	322	(1)
Glossary	323	(1)
Key Formulas	324	(1)
Supplementary Exercises	324	(3)
Case Problem 1 Bock Investment Services	327	(1)
Case Problem 2 Gulf Real Estate Properties	327	(3)
Case Problem 3 Metropolitan Research, Inc.	330	(1)
Appendix 8.1 Interval Estimation with Minitab	331	(1)
Appendix 8.2 Interval Estimation Using Excel	332	(4)
Chapter 9 Hypothesis Testing	336	(57)
Statistics in Practice: John Morrell & Company	337	(1)
9.1 Developing Null and Alternative Hypotheses	338	(2)
Testing Research Hypotheses	338	(1)
Testing the Validity of a Claim	338	(1)
Testing in Decision-Making Situations	339	(1)
Summary of Forms for Null and Alternative Hypotheses	339	(1)
9.2 Type I and Type II Errors	340	(3)
9.3 Population Mean: σ Known	343	(15)
One-Tailed Test	343	(6)
Two-Tailed Test	349	(3)
Summary and Practical Advice	352	(1)
Relationship Between Interval Estimation and Hypothesis Testing	353	(5)
9.4 Population Mean: σ Unknown	358	(7)
One-Tailed Test	358	(2)
Two-Tailed Test	360	(1)
Summary and Practical Advice	361	(4)
9.5 Population Proportion	365	(5)
Summary	367	(3)
9.6 Hypothesis Testing and Decision Making	370	(1)
9.7 Calculating the Probability of Type II Errors	371	(5)
9.8 Determining the Sample Size for Hypothesis Test About a Population Mean	376	(4)
Summary	380	(1)
Glossary	380	(1)
Key Formulas	381	(1)
Supplementary Exercises	381	(3)
Case Problem 1 Quality Associates, Inc.	384	(1)
Case Problem 2 Unemployment Study	385	(1)
Appendix 9.1 Hypothesis Testing with Minitab	386	(2)
Appendix 9.2 Hypothesis Testing with Excel	388	(5)
Chapter 10 Statistical Inference About Means and Proportions with Two Populations	393	(39)
Statistics in Practice: Fisons Corporation	394	(1)
10.1 Inferences About the Difference Between Two Population Means: σl and σ2, Known	395	(7)
Interval Estimate of μ1-μ2	395	(2)
Hypothesis Tests About μ1-μ2	397	(2)
Practical Advice	399	(3)
10.2 Inferences About the Difference Between Two Population Means: σl and σ2 Unknown	402	(9)
Interval Estimation of μ1-μ2	402	(1)
Hypothesis Tests About μ1-μ2	403	(2)
Practical Advice	405	(6)
10.3 Inferences About the Difference Between Two Population Means: Matched Samples	411	(6)
10.4 Inferences About the Difference Between Two Population Proportions	417	(5)
Interval Estimation of ρ1-ρ2	417	(2)
Hypothesis Tests About μ1-μ2	419	(3)
Summary	422	(1)
Glossary	423	(1)
Key Formulas	423	(2)
Supplementary Exercises	425	(2)
Case Problem Par, Inc.	427	(1)
Appendix 10.1 Inferences About Two Populations Using Minitab	428	(2)
Appendix 10.2 Inferences About Two Populations Using Excel	430	(2)
Chapter 11 Inferences About Population Variances	432	(25)
Statistics in Practice: U.S. General Accounting Office	433	(1)
11.1 Inferences About a Population Variance	434	(9)
Interval Estimation	434	(4)
Hypothesis Testing	438	(5)
11.2 Inferences About Two Population Variances	443	(7)
Summary	450	(1)
Key Formulas	450	(1)
Supplementary Exercises	451	(1)
Case Problem Air Force Training Program	452	(2)
Appendix 11.1 Population Variances with Minitab	454	(1)
Appendix 11.2 Population Variances with Excel	455	(2)
Chapter 12 Tests of Goodness of Fit and Independence	457	(33)
Statistics in Practice: United Way	458	(1)
12.1 Goodness of Fit Test: A Multinomial Population	459	(5)
12.2 Test of Independence	464	(7)
12.3 Goodness of Fit Test: Poisson and Normal Distributions	471	(10)
Poisson Distribution	472	(3)
Normal Distribution	475	(6)
Summary	481	(1)
Glossary	481	(1)
Key Formulas	481	(1)
Supplementary Exercises	482	(3)
Case Problem A Bipartisan Agenda for Change	485	(1)
Appendix 12.1 Tests of Goodness of Fit and Independence Using Minitab	486	(1)
Appendix 12.2 Tests of Goodness of Fit and Independence Using Excel	487	(3)
Chapter 13 Analysis of Variance and Experimental Design	490	(63)
Statistics in Practice: Burke Marketing Services, Inc.	491	(1)
13.1 An Introduction to Analysis of Variance	491	(4)
Assumptions for Analysis of Variance	493	(1)
A Conceptual Overview	493	(2)
13.2 Analysis of Variance: Testing for the Equality of k Population Means	495	(10)
Between-Treatments Estimate of Population Variance	496	(1)
Within-Treatments Estimate of Population Variance	497	(1)
Comparing the Variance Estimates: The F Test	498	(2)
ANOVA Table	500	(1)
Computer Results for Analysis of Variance	500	(5)
13.3 Multiple Comparison Procedures	505	(6)
Fisher's LSD	506	(2)
Type I Error Rates	508	(3)
13.4 An Introduction to Experimental Design	511	(2)
Data Collection	512	(1)
13.5 Completely Randomized Designs	513	(6)
Between-Treatments Estimate of Population Variance	514	(1)
Within-Treatments Estimate of Population Variance	514	(1)
Comparing the Variance Estimates: The F Test 514
ANOVA Table	515	(1)
Pairwise Comparisons	515	(4)
13.6 Randomized Block Design	519	(7)
Air Traffic Controller Stress Test	520	(1)
ANOVA Procedure	521	(1)
Computations and Conclusions	522	(4)
13.7 Factorial Experiments	526	(8)
ANOVA Procedure	527	(1)
Computations and Conclusions	528	(6)
Summary	534	(1)
Glossary	534	(1)
Key Formulas	535	(2)
Supplementary Exercises	537	(8)
Case Problem 1 Wentworth Medical Center	545	(1)
Case Problem 2 Compensation for ID Professionals	546	(1)
Appendix 13.1 Analysis of Variance and Experimental Design with Minitab	547	(1)
Appendix 13.2 Analysis of Variance and Experimental Design with Excel	548	(5)
Chapter 14 Simple Linear Regression	553	(82)
Statistics in Practice: Alliance Data Systems	554	(1)
14.1 Simple Linear Regression Model	555	(3)
Regression Model and Regression Equation	555	(1)
Estimated Regression Equation	556	(2)
14.2 Least Squares Method	558	(11)
14.3 Coefficient of Determination	569	(7)
Correlation Coefficient	572	(4)
14.4 Model Assumptions	576	(2)
14.5 Testing for Significance	578	(9)
Estimate of σ2	578	(1)
t Test	579	(1)
Confidence Interval for β1	580	(1)
F Test	581	(2)
Some Cautions About the Interpretation of Significance Tests	583	(4)
14.6 Using the Estimated Regression Equation for Estimation and Prediction	587	(6)
Point Estimation	587	(1)
Interval Estimation	587	(1)
Confidence Interval for the Mean Value of y	588	(1)
Prediction Interval for an Individual Value of y	589	(4)
14.7 Computer Solution	593	(5)
14.8 Residual Analysis: Validating Model Assumptions	598	(9)
Residual Plot Against x	599	(1)
Residual Plot Against y	600	(1)
Standardized Residuals	600	(3)
Normal Probability Plot	603	(4)
14.9 Residual Analysis: Outliers and Influential Observations	607	(7)
Detecting Outliers	607	(2)
Detecting Influential Observations	609	(5)
Summary	614	(1)
Glossary	615	(1)
Key Formulas	616	(2)
Supplementary Exercises	618	(5)
Case Problem 1 Spending and Student Achievement	623	(2)
Case Problem 2 U.S. Department of Transportation	625	(1)
Case Problem 3 Alumni Giving	626	(2)
Case Problem 4 Major League Baseball Team Values	628	(1)
Appendix 14.1 Calculus-Based Derivation of Least Squares Formulas	629	(1)
Appendix 14.2 A Test for Significance Using Correlation	630	(1)
Appendix 14.3 Regression Analysis with Minitab	631	(1)
Appendix 14.4 Regression Analysis with Excel	632	(3)
Chapter 15 Multiple Regression	635	(68)
Statistics in Practice: International Paper	636	(1)
15.1 Multiple Regression Model	637	(1)
Regression Model and Regression Equation	637	(1)
Estimated Multiple Regression Equation	637	(1)
15.2 Least Squares Method	638	(8)
An Example: Butler Trucking Company	639	(2)
Note on Interpretation of Coefficients	641	(5)
15.3 Multiple Coefficient of Determination	646	(3)
15.4 Model Assumptions	649	(1)
15.5 Testing for Significance	650	(8)
F Test	651	(3)
t Test	654	(1)
Multicollinearity	654	(4)
15.6 Using the Estimated Regression Equation for Estimation and Prediction	658	(2)
15.7 Qualitative Independent Variables	660	(8)
An Example: Johnson Filtration, Inc.	660	(2)
Interpreting the Parameters	662	(2)
More Complex Qualitative Variables	664	(4)
15.8 Residual Analysis	668	(7)
Detecting Outliers	669	(1)
Studentized Deleted Residuals and Outliers	670	(1)
Influential Observations	671	(1)
Using Cook's Distance Measure to Identify Influential Observations	671	(4)
15.9 Logistic Regression	675	(12)
Logistic Regression Equation	676	(1)
Estimating the Logistic Regression Equation	677	(2)
Testing for Significance	679	(1)
Managerial Use	680	(1)
Interpreting the Logistic Regression Equation	680	(3)
Logit Transformation	683	(4)
Summary	687	(1)
Glossary	687	(1)
Key Formulas	688	(2)
Supplementary Exercises	690	(5)
Case Problem 1 Consumer Research, Inc.	695	(1)
Case Problem 2 NFL Quarterback Rating	696	(2)
Case Problem 3 Predicting Student Proficiency Test Scores	698	(1)
Case Problem 4 Alumni Giving	699	(1)
Appendix 15.1 Multiple Regression with Minitab	699	(1)
Appendix 15.2 Multiple Regression with Excel	699	(3)
Appendix 15.3 Logistic Regression with Minitab	702	(1)
Chapter 16 Regression Analysis: Model Building	703	(54)
Statistics in Practice: Monsanto Company	704	(1)
16.1 General Linear Model	705	(15)
Modeling Curvilinear Relationships	705	(4)
Interaction	709	(2)
Transformations Involving the Dependent Variable	711	(4)
Nonlinear Models That Are Intrinsically Linear	715	(5)
16.2 Determining When to Add or Delete Variables	720	(7)
General Case	722	(1)
Use of ρ-Values	723	(4)
16.3 Analysis of a Larger Problem	727	(3)
16.4 Variable Selection Procedures	730	(7)
Stepwise Regression	731	(1)
Forward Selection	732	(1)
Backward Elimination	733	(1)
Best-Subsets Regression	733	(1)
Making the Final Choice	734	(3)
16.5 Residual Analysis	737	(7)
Autocorrelation and the Durbin-Watson Test	738	(6)
16.6 Multiple Regression Approach to Analysis of Variance and Experimental Design	744	(4)
Summary	748	(1)
Glossary	748	(1)
Key Formulas	749	(1)
Supplementary Exercises	749	(4)
Case Problem 1 Unemployment Study	753	(2)
Case Problem 2 Fuel Economy for Cars	755	(1)
Case Problem 3 Predicting Graduation Rates for Colleges and Universities	755	(2)
Chapter 17 Index Numbers	757	(21)
Statistics in Practice: U.S. Department of Labor, Bureau of Labor Statistics	758	(1)
17.1 Price Relatives	759	(1)
17.2 Aggregate Price Indexes	759	(4)
17.3 Computing an Aggregate Price Index from Price Relatives	763	(2)
17.4 Some Important Price Indexes	765	(2)
Consumer Price Index	765	(1)
Producer Price Index	765	(1)
Dow Jones Averages	766	(1)
17.5 Deflating a Series By Price Indexes	767	(4)
17.6 Price Indexes: Other Considerations	771	(1)
Selection of Items	771	(1)
Selection of a Base Period	771	(1)
Quality Changes	771	(1)
17.7 Quantity Indexes	772	(2)
Summary	774	(1)
Glossary	774	(1)
Key Formulas	774	(1)
Supplementary Exercises	775	(3)
Chapter 18 Forecasting	778	(47)
Statistics in Practice: Nevada Occupational Health Clinic	779	(1)
18.1 Components of a Time Series	780	(3)
Trend Component	780	(2)
Cyclical Component	782	(1)
Seasonal Component	783	(1)
Irregular Component	783	(1)
18.2 Smoothing Methods	783	(10)
Moving Averages	783	(2)
Weighted Moving Averages	785	(2)
Exponential Smoothing	787	(6)
18.3 Trend Projection	793	(6)
18.4 Trend and Seasonal Components	799	(10)
Multiplicative Model	799	(1)
Calculating the Seasonal Indexes	800	(4)
Deseasonalizing the Time Series	804	(1)
Using the Deseasonalized Time Series to Identify Trend	804	(3)
Seasonal Adjustments	807	(1)
Models Based on Monthly Data	807	(1)
Cyclical Component	807	(2)
18.5 Regression Analysis	809	(2)
18.6 Qualitative Approaches	811	(1)
Delphi Method	811	(1)
Expert Judgment	812	(1)
Scenario Writing	812	(1)
Intuitive Approaches	812	(1)
Summary	812	(1)
Glossary	813	(1)
Key Formulas	814	(1)
Supplementary Exercises	814	(5)
Case Problem 1 Forecasting Food and Beverage Sales	819	(1)
Case Problem 2 Forecasting Lost Sales	820	(1)
Appendix 18.1 Forecasting with Minitab	821	(2)
Appendix 18.2 Forecasting with Excel	823	(2)
Chapter 19 Nonparametric Methods	825	(34)
Statistics in Practice: West Shell Realtors	826	(2)
19.1 Sign Test	828	(5)
Small-Sample Case	828	(2)
Large-Sample Case	830	(1)
Hypothesis Test About a Median	831	(2)
19.2 Wilcoxon Signed-Rank Test	833	(5)
19.3 Mann-Whitney-Wilcoxon Test	838	(8)
Small-Sample Case	838	(2)
Large-Sample Case	840	(6)
19.4 Kruskal-Wallis Test	846	(4)
19.5 Rank Correlation	850	(4)
Test for Significant Rank Correlation	852	(2)
Summary	854	(1)
Glossary	855	(1)
Key Formulas	855	(1)
Supplementary Exercises	856	(3)
Chapter 20 Statistical Methods for Quality Control	859	(30)
Statistics in Practice: Dow Chemical U.S.A.	860	(1)
20.1 Statistical Process Control	861	(14)
Control Charts	862	(1)
x Chart: Process Mean and Standard Deviation Known	863	(2)
x Chart: Process Mean and Standard Deviation Unknown	865	(2)
R Chart	867	(2)
ρ Chart	869	(3)
nρ Chart	872	(1)
Interpretation of Control Charts	872	(3)
20.2 Acceptance Sampling	875	(9)
KALI, Inc.: An Example of Acceptance Sampling	876	(1)
Computing the Probability of Accepting a Lot	877	(3)
Selecting an Acceptance Sampling Plan	880	(1)
Multiple Sampling Plans	881	(3)
Summary	884	(1)
Glossary	884	(1)
Key Formulas	885	(1)
Supplementary Exercises	886	(2)
Appendix 20.1 Control Charts with Minitab	888	(1)
Chapter 21 Decision Analysis	889	(37)
Statistics in Practice: Ohio Edison Company	890	(1)
21.1 Problem Formulation	891	(2)
Payoff Tables	892	(1)
Decision Trees	892	(1)
21.2 Decision Making with Probabilities	893	(8)
Expected Value Approach	893	(2)
Expected Value of Perfect Information	895	(6)
21.3 Decision Analysis with Sample Information	901	(11)
Decision Tree	902	(1)
Decision Strategy	903	(3)
Expected Value of Sample Information	906	(6)
21.4 Computing Branch Probabilities Using Bayes' Theorem	912	(4)
Summary	916	(1)
Glossary	917	(1)
Key Formulas	918	(1)
Case Problem Lawsuit Defense Strategy	918	(1)
Appendix 21.1 Solving the PDC Problem with TreePlan	919
Chapter 22 Sample Survey On CD
Appendix A References and Bibliography	926	(2)
Appendix B Tables	928	(29)
Appendix C Summation Notation	957	(2)
Appendix D Self-Test Solutions and Answers to Even-Numbered Exercises	959	(51)
Index	1010