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Statistics for Business and Economics,9780130272935
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Statistics for Business and Economics

by ; ;
ISBN13:

9780130272935

ISBN10:
0130272930
Format:
Hardcover
Pub. Date:
1/1/2001
Publisher(s):
PRENTICE HALL
List Price: $113.00
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Summary

This best-selling introduction stresses the development of statistical thinking - the assessment of credibility and value of the inferences made from data - by both those who consume and those who produce the information. The authors emphasize inference; data collection and analysis are covered extensively, as needed, to evaluate the reported results of statistical studies and to make good business decisions. Numerous case studies, examples, and exercises draw on real business situations and recent economic events. Assumes a background in basic algebra. &

Table of Contents

Preface xiii
Statistics, Data, and Statistical Thinking
1(26)
The Science of Statistics
2(1)
Types of Statistical Applications in Business
2(2)
Fundamental Elements of Statistics
4(5)
Processes (Optional)
9(4)
Types of Data
13(2)
Quality Improvement: U.S. Firms Respond to the Challenge from Japan
14(1)
Collecting Data
15(3)
The Role of Statistics in Managerial Decision-Making
18(9)
A 20/20 View of Survey Results: Fact or Fiction?
20(1)
Quick Review
21(6)
Methods for Describing Sets of Data
27(92)
Describing Qualitative Data
28(10)
Pareto Analysis
30(8)
Graphical Methods for Describing Quantitative Data
38(14)
Summation Notation
52(2)
Numerical Measures of Central Tendency
54(11)
Numerical Measures of Variability
65(7)
Interpreting the Standard Deviation
72(8)
Numerical Measures of Relative Standing
80(6)
Methods for Detecting Outliers (Optional)
86(10)
Graphing Bivariate Relationships (Optional)
96(3)
The Time Series Plot (Optional)
99(3)
Distorting the Truth with Descriptive Techniques
102(17)
Car & Driver's ``Road Test Digest''
106(1)
Quick Review
107(10)
The Kentucky Milk Case---Part I (A Case Covering Chapters 1 and 2)
117(2)
Probability
119(50)
Events, Samples Spaces, and Probability
120(13)
Game Show Strategy: To Switch or Not to Switch?
130(3)
Unions and Intersections
133(3)
Complementary Events
136(2)
The Additive Rule and Mutually Exclusive Events
138(5)
Conditional Probability
143(4)
The Multiplicative Rule and Independent Events
147(10)
Random Sampling
157(12)
Lottery Buster
158(4)
Quick Review
162(7)
Discrete Random Variables
169(44)
Two Types of Random Variables
170(3)
Probability Distributions for Discrete Random Variables
173(5)
Expected Values of Discrete Random Variables
178(8)
Portfolio Selection
182(4)
The Binomial Random Variable
186(15)
The Space Shuttle Challenger: Catastrophe in Space
196(5)
The Poisson Random Variable (Optional)
201(12)
Quick Review
208(5)
Continuous Random Variables
213(44)
Continuous Probability Distributions
214(1)
The Uniform Distribution (Optional)
215(4)
The Normal Distribution
219(15)
IQ, Economic Mobility, and the Bell Curve
230(4)
Descriptive Methods for Assessing Normality
234(5)
Approximating a Binomial Distribution with a Normal Distribution
239(7)
The Exponential Distribution (Optional)
246(11)
Queueing Theory
250(2)
Quick Review
252(5)
Sampling Distributions
257(30)
The Concept of Sampling Distributions
258(7)
Properties of Sampling Distributions: Unbiasedness and Minimum Variance (Optional)
265(5)
Reducing Investment Risk Through Diversification
268(2)
The Central Limit Theorem
270(17)
The Insomnia Pill
276(3)
Quick Review
279(6)
The Furniture Fire Case (A Case Covering Chapters 3--6)
285(2)
Inferences Based on a Single Sample: Estimation with Confidence Intervals
287(52)
Large-Sample Confidence Interval for a Population Mean
288(9)
Small-Sample Confidence Interval for a Population Mean
297(12)
Scallops, Sampling, and the Law
303(6)
Large-Sample Confidence Interval for a Population Proportion
309(7)
Determining the Sample Size
316(7)
Finite Population Correction for Simple Random Sampling (Optional)
323(4)
Sample Survey Designs (Optional)
327(12)
Sampling Error Versus Nonsampling Error
328(3)
Quick Review
331(8)
Inferences Based on a Single Sample: Tests of Hypothesis
339(54)
The Elements of a Test of Hypothesis
340(6)
Large-Sample Test of Hypothesis About a Population Mean
346(8)
Statistical Quality Control
349(5)
Observed Significance Levels: p-Values
354(6)
Small-Sample Test of Hypothesis About a Population Mean
360(8)
Large-Sample Test of Hypothesis About a Population Proportion
368(6)
Calculating Type II Error Probabilities: More About β (Optional)
374(8)
Test of Hypothesis About a Population Variance (Optional)
382(11)
March Madness---Handicapping the NCAA Basketball Tourney
384(4)
Quick Review
388(5)
Inferences Based on Two Samples: Confidence Intervals And Tests of Hypotheses
393(62)
Comparing Two Population Means: Independent Sampling
394(18)
The Effect of Self-Managed Work Teams on Family Life
402(10)
Comparing Two Population Means: Paired Difference Experiments
412(12)
Comparing Two Population Proportions: Independent Sampling
424(7)
Determining the Sample Size
431(4)
Unpaid Overtime and the Fair Labor Standards Act
432(3)
Comparing Two Population Variances: Independent Sampling (Optional)
435(20)
Quick Review
445(8)
The Kentucky Milk Case---Part II (A Case Covering Chapters 7--9)
453(2)
Simple Linear Regression
455(78)
Probabilistic Models
456(4)
Fitting the Model: The Least Squares Approach
460(13)
Model Assumptions
473(1)
An Estimator of σ2
474(4)
Assessing the Utility of the Model: Making Inferences About the Slope β1
478(11)
The Coefficient of Correlation
489(4)
The Coefficient of Determination
493(7)
Using the Model for Estimation and Prediction
500(14)
Statistical Assessment of Damage to Bronx Bricks
504(10)
Simple Linear Regression: A Complete Example
514(19)
Can ``Dowsers'' Really Detect Water?
518(3)
Quick Review
521(12)
Multiple Regression and Model Building
533(142)
Multiple Regression Models
534(1)
The First-Order Model: Estimating and Interpreting the β-Parameters
535(6)
Model Assumptions
541(3)
Inferences About the β Parameters
544(10)
Checking the Overall Utility of a Model
554(15)
Predicting the Price of Vintage Red Bordeaux Wine
560(9)
Using the Model for Estimation and Prediction
569(5)
Model Building: Interaction Models
574(8)
Model Building: Quadratic and Other Higher-Order Models
582(12)
Model Building: Qualitative (Dummy) Variable Models
594(8)
Model Building: Models with Both Quantitative and Qualitative Variables (Optional)
602(12)
Model Building: Comparing Nested Models (Optional)
614(12)
Model Building: Stepwise Regression (Optional)
626(8)
Residual Analysis: Checking the Regression Assumptions
634(15)
Some Pitfalls: Estimability, Multicollinearity, and Extrapolation
649(26)
``Wringing'' The Bell Curve
652(8)
Quick Review
660(15)
Methods for Quality Improvement
675(76)
Quality, Processes, and Systems
676(6)
Deming's 14 Points
680(2)
Statistical Control
682(8)
The Logic of Control Charts
690(5)
A Control Chart for Monitoring the Mean of a Process: The x-Chart
695(17)
A Control Chart for Monitoring the Variation of a Process: The R-Chart
712(11)
A Control Chart for Monitoring the Proportion of Defectives Generated by a Process: The p-Chart
723(9)
Diagnosing the Causes of Variation (Optional)
732(6)
Quality Control in a Service Operation
736(2)
Capability Analysis (Optional)
738(13)
Quick Review
744(7)
Time Series: Descriptive Analyses, Models, and Forecasting
751(64)
Descriptive Analysis: Index Numbers
752(13)
The Consumer Price Index: CPI-U and CPI-W
760(5)
Descriptive Analysis: Exponential Smoothing
765(5)
Time Series Components
770(1)
Forecasting: Exponential Smoothing
771(3)
Forecasting Trends: The Holt-Winters Forecasting Model (Optional)
774(7)
Measuring Forecast Accuracy: MAD and RMSE
781(3)
Forecasting Trends: Simple Linear Regression
784(3)
Seasonal Regression Models
787(9)
Forecasting the Demand for Emergency Room Services
788(8)
Autocorrelation and the Durbin-Watson Test
796(19)
Quick Review
803(7)
The Gasket Manufacturing Case (A Case Covering Chapters 12 and 13)
810(5)
Design of Experiments and Analysis of Variance
815(72)
Elements of a Designed Experiment
816(5)
The Completely Randomized Design: Single Factor
821(18)
Multiple Comparisons of Means
839(9)
Is Therapy the New Diet Pill for Binge Eaters?
844(4)
Factorial Experiments
848(18)
On the Trail of the Cockroach
860(6)
Using Regression Analysis for ANOVA (Optional)
866(21)
Quick Review
876(11)
Nonparametric Statistics
887(48)
Introduction: Distribution-Free Tests
888(1)
Single Population Inferences: The Sign Test
889(5)
Comparing Two Populations: The Wilcoxon Rank Sum Test for Independent Samples
894(9)
Comparing Two Populations: The Wilcoxon Signed Rank Test for the Paired Difference Experiment
903(8)
Reanalyzing the Scallop Weight Data
908(3)
The Kruskal-Wallis H-Test for a Completely Randomized Design
911(8)
Taxpayers Versus the IRS: Selecting the Trial Court
915(4)
Spearman's Rank Correlation Coefficient
919(16)
Quick Review
928(7)
Categorical Data Analysis
935(73)
Categorical Data and The Multinomial Experiment
936(1)
Testing Category Probabilities: One-way Table
937(7)
Testing Category Probabilities: Two-way (Contingency) Table
944(16)
Ethics in Computer Technology and Use
956(4)
A Word of Caution About Chi-Square Tests
960(10)
Quick Review
961(7)
Discrimination in the Workplace (A Case Covering Chapters 14--16)
968(2)
APPENDICES
Appendix A Basic Counting Rules
970(3)
Appendix B Tables
973(33)
Appendix C Calculation Formulas for Analysis of Variance
1006(2)
Answers to Selected Exercises 1008(9)
References 1017(5)
Index 1022


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