CART

(0) items

Statistics for Business and Economics,9780138402327
This item qualifies for
FREE SHIPPING!

FREE SHIPPING OVER $59!

Your order must be $59 or more, you must select US Postal Service Shipping as your shipping preference, and the "Group my items into as few shipments as possible" option when you place your order.

Bulk sales, PO's, Marketplace Items, eBooks, Apparel, and DVDs not included.

Statistics for Business and Economics

by
ISBN13:

9780138402327

ISBN10:
0138402329
Format:
Hardcover
Pub. Date:
11/1/1997
Publisher(s):
Prentice Hall
List Price: $96.00

Buy New Textbook

Currently Available, Usually Ships in 24-48 Hours
N9780138402327
$92.20

Rent Textbook

We're Sorry
Sold Out

Used Textbook

We're Sorry
Sold Out

eTextbook

We're Sorry
Not Available

More New and Used
from Private Sellers
Starting at $0.01
See Prices

Questions About This Book?

What version or edition is this?
This is the edition with a publication date of 11/1/1997.
What is included with this book?
  • The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any CDs, lab manuals, study guides, etc.

Related Products


  • Excel Manual for Statistics for Business and Economics
    Excel Manual for Statistics for Business and Economics
  • Statistics for Business and Economics
    Statistics for Business and Economics
  • Statistics for Business and Economics
    Statistics for Business and Economics
  • Statistics for Business and Economics
    Statistics for Business and Economics
  • Statistics for Business and Economics
    Statistics for Business and Economics
  • Statistics for Business and Economics
    Statistics for Business and Economics
  • Statistics for Business and Economics Plus NEW MyStatLab with Pearson eText -- Access Card Package
    Statistics for Business and Economics Plus NEW MyStatLab with Pearson eText -- Access Card Package
  • Statistics for Business and Economics, A La Carte Plus MyStatLab
    Statistics for Business and Economics, A La Carte Plus MyStatLab
  • Statistics for Business and Economics, Books a la Carte Edition
    Statistics for Business and Economics, Books a la Carte Edition
  • Statistics for Business and Economics, Student Value Edition
    Statistics for Business and Economics, Student Value Edition
  • Student's Solutions Manual for Statistics for Business and Economics
    Student's Solutions Manual for Statistics for Business and Economics
  • Student's Solutions Manual for Statistics for Business and Economics
    Student's Solutions Manual for Statistics for Business and Economics




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 ix
CHAPTER 1 Statistics, Data, and Statistical Thinking
1(24)
1.1 The Science of Statistics
2(1)
1.2 Types of Statistical Applications in Business
2(2)
1.3 Fundamental Elements of Statistics
4(5)
1.4 Processes (Optional)
9(3)
1.5 Types of Data
12(3)
STATISTICS IN ACTION 1.1 Quality Improvement: U.S. Firms Respond to the Challenge from Japan
13(2)
1.6 Collecting Data
15(2)
1.7 The Role of Statistics in Managerial Decision-Making
17(8)
STATISTICS IN ACTION 1.2 A 20/20 View of Survey Results: Fact or Fiction?
18(3)
Quick Review
21(4)
CHAPTER 2 Methods for Describing Sets of Data
25(86)
2.1 Describing Qualitative Data
26(9)
STATISTICS IN ACTION 2.1 Pareto Analysis
31(4)
2.2 Graphical Methods for Describing Quantitative Data
35(14)
2.3 The Time Series Plot (Optional)
49(3)
2.4 Summation Notation
52(1)
2.5 Numerical Measures of Central Tendency
53(10)
2.6 Numerical Measures of Variability
63(6)
2.7 Interpreting the Standard Deviation
69(7)
2.8 Numerical Measures of Relative Standing
76(7)
2.9 Quartiles and Box Plots (Optional)
83(7)
2.10 Graphing Bivariate Relationship (Optional)
90(3)
2.11 Distorting the Truth with Descriptive Techniques
93(18)
STATISTICS IN ACTION 2.2 Car & Driver's "Road Test Digest"
93(5)
Quick Review
98(9)
SHOWCASE The Kentucky Milk Case--Part I
107(2)
INTERNET LAB Accessing and Summarizing Business and Economic Data Maintained by the U.S. Government
109(2)
CHAPTER 3 Probability
111(50)
3.1 Events, Sample Spaces, and Probability
112(14)
STATISTICS IN ACTION 3.1 Game Show Strategy: To Switch or Not to Switch
122(4)
3.2 Unions and Intersections
126(2)
3.3 Complementary Events
128(1)
3.4 The Additive Rule and Mutually Exclusive Events
129(6)
3.5 Conditional Probability
135(3)
3.6 The Multiplicative Rule and Independent Events
138(10)
3.7 Random Sampling
148(13)
STATISTICS IN ACTION 3.2 Lottery Buster
151(2)
Quick Review
153(8)
CHAPTER 4 Discrete Random Variables
161(40)
4.1 Two Types of Random Variables
162(3)
4.2 Probability Distributions for Discrete Random Variables
165(5)
4.3 Expected Values of Discrete Random Variables
170(8)
STATISTICS IN ACTION 4.1 Portfolio Selection
174(13)
STATISTICS IN ACTION 4.2 The Space Shuttle Challenger: Catastrophe in Space
187
4.4 The Binomial Random Variable
178(12)
4.5 The Poisson Random Variable (Optional)
190(11)
Quick Review
195(6)
CHAPTER 5 Continuous Random Variables
201(38)
5.1 Continuous Probability Distributions
202(1)
5.2 The Uniform Distribution (Optional)
203(4)
5.3 The Normal Distribution
207(14)
STATISTICS IN ACTION 5.1 IQ, Economic Mobility, and the Bell Curve
216(5)
5.4 Approximating a Binomial Distribution with a Normal Distribution
221(6)
5.5 The Exponential Distribution (Optional)
227(12)
STATISTICS IN ACTION 5.2 Queueing Theory
230(3)
Quick Review
233(6)
CHAPTER 6 Sampling Distributions
239(30)
6.1 The Concept of Sampling Distributions
240(7)
6.2 Properties of Sampling Distributions: Unbiasedness and Minimum Variance
247(5)
STATISTICS IN ACTION 6.1 Reducing Investment Risk Through Diversification
250(2)
6.3 The Sampling Distribution of the Sample Mean
252(17)
STATISTICS IN ACTION 6.2 The Insomnia Pill
258(3)
Quick Review
261(6)
SHOWCASE The Furniture Fire Case
267(1)
INTERNET LAB Analyzing Monthly Business Start-ups
268(1)
CHAPTER 7 Inferences Based on a Single Sample: Estimation with Confidence Intervals
269(48)
7.1 Large-Sample Confidence Interval for a Population Mean
270(8)
7.2 Small-Sample Confidence Interval for a Population Mean
278(10)
STATISTICS IN ACTIONS 7.1 Scallops, Sampling, and the Law
284(4)
7.3 Large-Sample Confidence Interval for a Population Proportion
288(5)
7.4 Determining the Sample Size
293(8)
STATISTICS IN ACTION 7.2 Is Caffeine Addictive?
299(2)
7.5 Finite Population Correction for Simple Random Sampling (Optional)
301(3)
7.6 Sample Survey Designs (Optional)
304(13)
STATISTICS IN ACTION 7.3 Sampling Error Versus Nonsampling Error
307(2)
Quick Review
309(8)
CHAPTER 8 Inferences Based on a Single Sample: Tests of Hypothesis
317(50)
8.1 The Elements of a Test of Hypothesis
318(6)
STATISTICS IN ACTION 8.1 Statistics Is Murder!
322(2)
8.2 Large-Sample Test of Hypothesis About a Population Mean
324(8)
STATISTICS IN ACTION 8.2 Statistical Quality Control, Part I
328(4)
8.3 Observed Significance Levels: p-Values
332(6)
8.4 Small-Sample Test of Hypothesis About a Population Mean
338(7)
8.5 Large-Sample Test of Hypothesis About a Population Proportion
345(7)
STATISTICS IN ACTION 8.3 Statistical Quality Control, Part II
349(3)
8.6 Calculating Type II Error Probabilities: More About XXX (Optional)
352(15)
Quick Review
361(6)
CHAPTER 9 Inferences Based on Two Samples: Confidence Intervals and Tests of Hypotheses
367(62)
9.1 Comparing Two Population Means: Independent Sampling
368(19)
STATISTICS IN ACTION 9.1 The Effect of Self-Managed Work Teams on Family Life
378(9)
9.2 Comparing Two Population Means: Paired Difference Experiments
387(10)
9.3 Comparing Two Population Proportions: Independent Sampling
397(7)
9.4 Determining the Sample Size for Comparing Means or Proportions
404(4)
STATISTICS IN ACTION 9.2 Unpaid Overtime and the Fair Labor Standards Act
406(2)
9.5 Comparing Two Population Variances: Independent Sampling
408(21)
Quick Review
418(9)
SHOWCASE The Kentucky Milk Case--Part II
427(1)
INTERNET LAB Choosing Between Economic Indicators
428(1)
CHAPTER 10 Simple Linear Regression
429(70)
10.1 Probabilistic Models
430(3)
10.2 Fitting the Model: The Least Squares Approach
433(11)
10.3 Model Assumptions
444(1)
10.4 An Estimator of XXX(2)
445(6)
10.5 Assessing the Utility of the Model: Making Inferences About the Slope XXX(1)
451(10)
STATISTICS IN ACTION 10.1 New Jersey Banks--Serving Minorities?
454(7)
10.6 The Coefficient of Correlation
461(3)
10.7 The Coefficient of Determination
464(8)
10.8 Using the Model for Estimation and Prediction
472(12)
STATISTICS IN ACTION 10.2 Statistical Assessment of Damage to Bronx Bricks
478(6)
10.9 Simple Linear Regression: An Example
484(15)
Quick Review
487(12)
CHAPTER 11 Multiple Regression
499(78)
11.1 Multiple Regression: The Model and the Procedure
500(1)
11.2 Fitting the Model: The Least Squares Approach
501(3)
11.3 Model Assumptions
504(2)
11.4 Inferences About the XXX Parameters
506(11)
11.5 Checking the Usefulness of a Model: R(2) and the Analysis of Variance F-Test
517(15)
11.6 Using the Model for Estimation and Prediction
532(2)
11.7 Multiple Regression: An Example
534(3)
11.8 Residual Analysis: Checking the Regression Assumptions
537(13)
STATISTICS IN ACTION 11.1 Predicting the Price of Vintage Red Bordeaux Wine
538(12)
11.9 Some Pitfalls: Estimability, Multicollinearity, and Extrapolation
550(27)
STATISTICS IN ACTION 11.2 "Wringing" The Bell Curve
553(9)
Quick Review
562(15)
CHAPTER 12 Model Building
577(84)
12.1 Introduction
578(1)
12.2 The Two Types of Independent Variables: Quantitative and Qualitative
579(2)
12.3 Models with a Single Quantitative Independent Variable
581(9)
12.4 Models with Two or More Quantitative Independent Variables
590(8)
12.5 Testing Portions of a Model
598(12)
12.6 Models with One Qualitative Independent Variable
610(9)
12.7 Comparing the Slopes of Two or More Lines
619(12)
12.8 Comparing Two or More Response Curves
631(12)
STATISTICS IN ACTION 12.1 Forecasting Peak-Hour Traffic Volume
633(10)
12.9 Stepwise Regression
643(18)
Quick Review
651(7)
SHOWCASE The Condo Sales Case
658(2)
INTERNET LAB Using the Consumer Price Index in Business Forecasts of Labor, Wages, and Compensation
660(1)
CHAPTER 13 Methods for Quality Improvement
661(72)
13.1 Quality, Processes, and Systems
662(6)
STATISTICS IN ACTION 13.1 Deming's 14 Points
666(2)
13.2 Statistical Control
668(8)
13.3 The Logic of Control Charts
676(4)
13.4 A Control Chart for Monitoring the Mean of a Process: The x-Chart
680(17)
13.5 A Control Chart for Monitoring the Variation of a Process: The R-Chart
697(9)
13.6 A Control Chart for Monitoring the Proportion of Defectives Generated by a Process: The p-Chart
706(9)
13.7 Diagnosing the Causes of Variation (Optional)
715(5)
STATISTICS IN ACTION 13.2 Quality Control in a Service Operation
719(1)
13.8 Capability Analysis (Optional)
720(13)
Quick Review
727(6)
CHAPTER 14 Time Series: Descriptive Analyses, Models, and Forecasting
733(66)
14.1 Descriptive Analysis: Index Numbers
734(14)
STATISTICS IN ACTION 14.1 The Consumer Price Index: CPI-U and CPI-W
743(5)
14.2 Descriptive Analysis: Exponential Smoothing
748(5)
14.3 Time Series Components
753(1)
14.4 Forecasting: Exponential Smoothing
754(3)
14.5 Forecasting Trends: The Holt-Winters Forecasting Model (Optional)
757(6)
14.6 Measuring Forecast Accuracy: MAD and RMSE
763(3)
14.7 Forecasting Trends: Simple Linear Regression
766(4)
STATISTICS IN ACTION 14.2 Forecasting the Demand for Emergency Room Services
770(1)
14.8 Seasonal Regression Models
770(8)
14.9 Autocorrelation and the Durbin-Watson Test
778(21)
Quick Review
786(7)
SHOWCASE The Gasket Manufacturing Case
793(4)
INTERNET LAB Quality Management Outside of Manufacturing Operation
797(2)
CHAPTER 15 Design of Experiments and Analysis of Variance
799(68)
15.1 Elements of a Designed Experiment
800(5)
15.2 The Completely Randomized Design: Single Factor
805(16)
15.3 Multiple Comparisons of Means
821(8)
STATISTICS IN ACTION 15.1 Is Therapy the New "Diet Pill" for Binge Eaters?
825(4)
15.4 Factorial Experiments
829(17)
STATISTICS IN ACTION 15.2 Improving a Ground Meat Canning Process Through Experimental Design
840(6)
15.5 Using Regression Analysis for ANOVA (Optional)
846(11)
Quick Review
857(10)
CHAPTER 16 Nonparametric Statistics
867(46)
16.1 Introduction
868(1)
16.2 Single Population Inferences: The Sign Test
869(5)
16.3 Comparing Two Populations: The Wilcoxon Rank Sum Test for Independent Samples
874(7)
16.4 Comparing Two Populations: The Wilcoxon Signed Rank Test for the Paired Difference Experiment
881(8)
STATISTICS IN ACTION 16.1 Reanalyzing the Scallop Weight Data
886(3)
16.5 The Kruskal-Wallis H-Test for a Completely Randomized Design
889(8)
STATISTICS IN ACTION 16.2 Taxpayers Versus the IRS: Selecting the Trial Court
893(4)
16.6 Spearman's Rank Correlation Coefficient
897(16)
Quick Review
906(7)
CHAPTER 17 The Chi-Square Test and the Analysis of Contingency Tables
913(34)
17.1 One-Dimensional Count Data: The Multinomial Distribution
914(7)
17.2 Contingency Tables
921(14)
STATISTICS IN ACTION 17.1 Ethics in Computer Technology and Use
928(7)
17.3 A Word of Caution About Chi-Square Tests
935(12)
Quick Review
935(9)
SHOWCASE Discrimination in the Workplace
944(2)
INTERNET LAB Sampling and Analyzing NYSE Stock Quotes
946(1)
CHAPTER 18 Decision Analysis
947(52)
18.1 Introduction
948(1)
18.2 Three Types of Decision Problems
949(2)
18.3 Decision-Making Under Uncertainty: Basic Concepts
951(4)
18.4 Two Ways of Expressing Outcomes: Payoffs and Opportunity Losses
955(4)
18.5 Characterizing the Uncertainty in Decision Problems
959(1)
18.6 Solving the Decision Problem Using the Expected Payoff Criterion
960(5)
STATISTICS IN ACTION 18.1 Evaluating Uncertainty in Research and Development
961(4)
18.7 The Expected Utility Criterion
965(4)
18.8 Classifying Decision-Makers by Their Utility Functions
969(5)
18.9 Revising State of Nature Probabilities: Bayes' Rule
974(5)
18.10 Solving Decision Problems Using Posterior Probabilities
979(4)
18.11 The Expected Value of Sample Information: Preposterior Analysis (Optional)
983(16)
STATISTICS IN ACTION 18.2 Hurricanes: To Seed or Not to Seed?
989(4)
Quick Review
993(6)
APPENDIX A Basic Counting Rules 999(4)
APPENDIX B Tables
1003(33)
APPENDIX C Calculation Formulas for Analysis of Variance 1036(2)
Answers to Selected Exercises 1038(13)
References 1051(6)
Index 1057


Please wait while the item is added to your cart...