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More About This Textbook
Overview
Statistics for Business and Economics, Twelfth Edition, meets today's business students with a balance of clarity and rigor, and applications incorporated from a diverse range of industries. This classic text covers a wide variety of data collection and analysis techniques with these goals in mind: developing statistical thinking, learning to assess the credibility and value of inferences made from data, and making informed business decisions.
The Twelfth Edition has been updated with real, current data in many of the exercises, examples, and applications. Exercises draw on actual business situations and recent economic events so that students can test their knowledge throughout the course. Statistics in Action case studies open each chapter with a recent, controversial, or highprofile business issue, motivating students to critically evaluate the findings and think through the statistical issues involved. A continued emphasis on ethics highlights the importance of ethical behavior in collecting, interpreting, and reporting on data.
Editorial Reviews
Booknews
For business students ready for total immersion in multiple regression analysis, model building, analysis of variance, and categorical data analysis, this iteration offers such highlights as exploring data with statistical computer software and the TI83 graphing calculator, "statistics in action" issues (e.g. ethics in computer technology and use), and realitybased exercises. Appends basic counting rules, statistical tables, analysis of variance formulas, and answers to selected exercises. Supplementary materials are available. Those who find this weighty text daunting may be relieved to know that a streamlined version, , for single semester courses is available. McClave is at the U. of Florida. No dates are furnished for previous editions. Annotation c. Book News, Inc., Portland, OR (booknews.com)Booknews
A new edition of an advanced undergraduate level text intended for students with a noncalculus background. Presents statistical theory and principles in the context of real business situations to encourage practical problemsolving. Also covers some of the technological tools available, including EXCEL, SPSS, SAS, or Minitab. MacIntosh or Windows data disk includes learning objectives, thinking challenges, concept presentation slides, and worked examples. Annotation c. by Book News, Inc., Portland, Or.Product Details
Related Subjects
Meet the Author
Dr. Jim McClave is currently President and CEO of Info Tech, Inc., a statistical consulting and software development firm with an international clientele. He is an Adjunct Professor of Statistics at the University of Florida, where he was a fulltime member of the faculty for 20 years.
P. George Benson is the 21st president of the College of Charleston. Prior to his appointment, he was Dean at the University of Georgia’s C. Herman and Mary Virginia Terry College of Business. His research interests include quality management, strategic management, belief formation, and judgmental forecasting. He consults nationally in the areas of applied statistics, quality management, and employment discrimination.
Terry Sincich obtained his PhD in statistics from the University of Florida in 1980. He is an Associate Professor in the Information Systems & Decision Sciences Department at the University of South Florida in Tampa. Dr. Sincich is responsible for teaching basic statistics to all undergraduates in the College of Business, as well as advanced statistics to all business doctoral candidates. He has published articles in such journals as the Journal of the American Statistical Association, International Journal of Forecasting, Academy of Management Journal, and Auditing: A Journal of Practice & Theory. Dr. Sincich is a coauthor of the texts Statistics, A First Course in Statistics, Statistics for Engineering & the Sciences, and A Second Course in Statistics: Regression Analysis.
Read an Excerpt
Preface
This eighth edition of Statistics for Business and Economics is an introductory business text emphasizing inference, with extensive coverage of data collection and analysis as needed to evaluate the reported results of statistical studies and to make good decisions. As in earlier editions, the text stresses the development of statistical thinking, the assessment of credibility and value of the inferences made from data, both by those who consume and those who produce them. It assumes a mathematical background of basic algebra.
A briefer version of the book, A First Course in Business Statistics, is available for single semester courses that include minimal coverage of regression analysis, analysis of variance, and categorical data analysis.
NEW IN THE EIGHTH EDITION
Major Content Changes
Chapter 2 includes two new optional sections: methods for detecting outliers (Section 2.8) and graphing bivariate relationships (Section 2.9).
Chapter 5 now covers descriptive methods for assessing whether a data set is approximately normally distributed.
Chapter 11 is a new multiple regression chapter. The material on multiple regression models and model building (Chapters 11 and 12 in previous editions) is reorganized into a single, streamlined chapter, with initial emphasis on the firstorder model. More complex models (e.g., interaction, quadratic, and dummy variable models) are presented in increasing order of difficulty. Coverage of residual analysis (Section 11.13) is expanded to include treatment of heteroscedastic errors.
Exploring Data withStatistical Computer Software and the Graphing Calculator—Throughout the text, computer printouts from four popular Windowsbased statistical software packages (SAS, SPSS, MINITAB, STATISTIX) are displayed and used to make decisions about the data. New to this edition, we have included instruction boxes and output for the TI83 graphing calculator.
Statistics in Action—One or two features per chapter examine current reallife, highprofile issues. Data from the study is presented for analysis. Questions prompt the students to form their own conclusions and to think through the statistical issues involved.
RealWorld Business Cases—Six extensive business problemsolving cases, with real data and assignments. Each case serves as a good capstone and review of the material that has preceded it.
RealData Exercises—Almost all the exercises in the text employ the use of current real data taken from a wide variety of publications (e.g., newspapers, magazines, and journals).
Quick Review—Each chapter ends with a list of key terms and formulas, with reference to the page number where they first appear.
Language Lab—Following the Quick Review is a pronunciation guide for Greek letters and other special terms. Usage notes are also provided.
TRADITIONAL STRENGTHS
We have maintained the features of Statistics for Business and Economics that we believe make it unique among business statistics texts. These features, which assist the student in achieving an overview of statistics and an understanding of its relevance in the business world and in everyday life, are as follows:
The Use of Examples as a Teaching Device
Almost all new ideas are introduced and illustrated by real databased applications and examples. We believe that students better understand definitions, generalizations, and abstractions after seeing an application.
Many Exercises—Labeled by Type
The text includes more than 1,400 exercises illustrated by applications in almost all areas of research. Because many students have trouble learning the mechanics of statistical techniques when problems are couched in terms of realistic applications, all exercise sections are divided into two parts:
A Choice in Level of Coverage of Probability (Chapter 3)
One of the most troublesome aspects of an introductory statistics course is the study of probability. Probability poses a challenge for instructors because they must decide on the level of presentation, and students find it a difficult subject to comprehend. We believe that one cause for these problems is the mixture of probability and counting rules that occurs in most introductory texts. We have included the counting rules in a separate and optional section at the end of the chapter on probability. In addition, all exercises that require the use of counting rules are marked with an asterisk (*). Thus, the instructor can control the level of coverage of probability.
Extensive Coverage of Multiple Regression Analysis
and Model Building (Chapter 11)
This topic represents one of the most useful statistical tools for the solution of applied problems. Although an entire text could be devoted to regression modeling, we believe we have presented coverage that is understandable, usable, and much more comprehensive than the presentations in other introductory statistics texts.
We devote three chapters to discussing the major types of inferences that can be derived from a regression analysis, showing how these results appear in computer printouts and, most important, selecting multiple regression models to be used in an analysis. Thus, the instructor has the choice of a onechapter coverage of simple regression, a twochapter treatment of simple and multiple regression, or a complete threechapter coverage of simple regression, multiple regression, and model building. This extensive coverage of such useful statistical tools will provide added evidence to the student of the relevance of statistics to the solution of applied problems.
Footnotes
Although the text is designed for students with a noncalculus background, footnotes explain the role of calculus in various derivations. Footnotes are also used to inform the student about some of the theory underlying certain results. The footnotes allow additional flexibility in the mathematical and theoretical level at which the material is presented.
SUPPLEMENTS FOR THE INSTRUCTOR
The supplements for the eighth edition have been completely revised to reflect the revisions of the text. To ensure adherence to the approaches presented in the main text, each element in the package has been accuracy checked for clarity, and freedom from computational, typographical, and statistical errors.
Annotated Instructor's Edition (AIE) (ISBN 0130279854)
Marginal notes placed next to discussions of essential teaching concepts include:
Instructor's Notes by Mark Dummeldinger (ISBN 0130274100)
This printed resource contains suggestions for using the questions at the end of the Statistics in Action boxes as the basis for class discussion on statistical ethics and other current issues, solutions to the RealWorld Cases, a complete short answer book with letter of permission to duplicate for student use, and many of the exercises and solutions that were removed from previous editions of this text.
Instructor's Solutions Manual by Nancy S. Boudreau
(ISBN 0130274216)
Solutions to all of the evennumbered exercises are given in this manual. Careful attention has been paid to ensure that all methods of solution and notation are consistent with those used in the core text. Solutions to the oddnumbered exercises are found in the Student's Solutions Manual.
Test Bank by Mark Dummeldinger (ISBN 0130274194)
Entirely rewritten, the Test Bank now includes more than 1,000 problems that correlate to problems presented in the text.
Test Gen EQ
PowerPoint Presentation Disk by Mark Dummeldinger
(ISBN 0130273651)
This versatile Windowsbased tool may be used by professors in a number of different ways:
Included on the software disk are learning objectives, thinking challenges, concept presentation slides, and examples with workedout solutions. The PowerPoint Presentation Disk may be downloaded from the FTP site found at the McClave Web site.
Data Disk—available free with every text purchased from Prentice Hall
The data sets for all exercises and cases are available on a 3 1/2" diskette in ASCII format in the back of the book. When a given data set is referenced, a disk symbol and the file name will appear in the text near the exercise.
McClave Internet Site (...
Table of Contents
1. Statistics, Data, and Statistical Thinking
1.1 The Science of Statistics
1.2 Types of Statistical Applications in Business
1.3 Fundamental Elements of Statistics
1.4 Processes (Optional)
1.5 Types of Data
1.6 Collecting Data: Sampling and Related Issues
1.7 Critical Thinking with Statistics
Statistics in Action: A 20/20 View of Surveys: Fact or Fiction?
Activity 1.1: Keep the Change: Collecting Data
Activity 2.2: Identifying Misleading Statistics
Using Technology: Accessing and Listing Data; Random Sampling
2. Methods for Describing Sets of Data
2.1 Describing Qualitative Data
2.2 Graphical Methods for Describing Quantitative Data
2.3 Numerical Measures of Central Tendency
2.4 Numerical Measures of Variability
2.5 Using the Mean and Standard Deviation to Describe Data
2.6 Numerical Measures of Relative Standing
2.7 Methods for Detecting Outliers: Box Plots and zScores
2.8 Graphing Bivariate Relationships (Optional)
2.9 The Time Series Plot (Optional)
2.10 Distorting the Truth with Descriptive Techniques
Statistics in Action: Can Money Buy Love?
Activity 2.1: Real Estate Sales
Activity 2.2: Keep the Change: Measures of Central Tendency and Variability
Using Technology: Describing Data
Making Business Decisions: The Kentucky Milk Case Part 1 (Covers Chapters 1 and 2)
3. Probability
3.1 Events, Sample Spaces, and Probability
3.2 Unions and Intersections
3.3 Complementary Events
3.4 The Additive Rule and Mutually Exclusive Events
3.5 Conditional Probability
3.6 The Multiplicative Rule and Independent Events
3.7 Bayes’s Rule
Statistics in Action: Lotto Buster!
Activity 3.1: Exit Polls: Conditional Probability
Activity 3.2: Keep the Change: Independent Events
Using Technology: Combinations and Permutations
4. Random Variables and Probability Distributions
4.1 Two Types of Random Variables
PART I: Discrete Random Variables
4.2 Probability Distributions for Discrete Random Variables
4.3 The Binomial Distribution
4.4 Other Discrete Distributions: Poisson and Hypergeometric
PART II: Continuous Random Variables
4.5 Probability Distributions for Continuous Random Variables
4.6 The Normal Distribution
4.7 Descriptive Methods for Assessing Normality
4.8 Other Continuous Distributions: Uniform and Exponential
Statistics in Action: Probability in a Reverse Cocaine Sting: Was Cocaine Really Sold?
Activity 4.1: Warehouse Club Memberships: Exploring a Binomial Random Variable
Activity 4.2: Identifying the Type of Probability Distribution
Using Technology: Discrete Probabilities, Continuous Probabilities, and Normal Probability Plots
5. Sampling Distributions
5.1 The Concept of a Sampling Distribution
5.2 Properties of Sampling Distributions: Unbiasedness and Minimum Variance
5.3 The Sampling Distribution of the Sample Mean and the Central Limit Theorem
5.4 The Sampling Distribution of the Sample Proportion
Statistics in Action: The Insomnia Pill: Is It Effective?
Activity 5.1: Simulating a Sampling Distribution Cell Phone Usage
Using Technology: Simulating a Sampling Distribution
Making Business Decisions: The Furniture Fire Case (Covers Chapters 3–5)
6. Inferences Based on a Single Sample: Estimation with Confidence Intervals
6.1 Identifying and Estimating the Target Parameter
6.2 Confidence Interval for a Population Mean: Normal (z) Statistic
6.3 Confidence Interval for a Population Mean: Student’s tStatistic
6.4 LargeSample Confidence Interval for a Population Proportion
6.5 Determining the Sample Size
6.6 Finite Population Correction for Simple Random Sampling (Optional)
6.7 Confidence Interval for a Population Variance (Optional)
Inferences Based on a Single Sample: Estimation with Confidence Intervals
Statistics in Action: Medicare Fraud Investigations
Activity 6.1: Conducting a Pilot Study
Using Technology: Confidence Intervals
7. Inferences Based on a Single Sample: Tests of Hypotheses
7.1 The Elements of a Test of Hypothesis
7.2 Formulating Hypotheses and Setting Up the Rejection Region
7.3 Observed Significance Levels: pValues
7.4 Test of Hypothesis about a Population Mean: Normal (z) Statistic
7.5 Test of Hypothesis about a Population Mean: Student’s tStatistic
7.6 LargeSample Test of Hypothesis about a Population Proportion
7.7 Test of Hypothesis about a Population Variance
7.8 Calculating Type II Error Probabilities: More about b (Optional)
Statistics in Action: Diary of a Kleenex^{®} User—How Many Tissues in a Box?
Activity 7.1: Challenging a Company's Claim: Tests of Hypotheses
Activity 7.2: Keep the Change: Tests of Hypotheses
Using Technology: Tests of Hypotheses
8. Inferences Based on Two Samples: Confidence Intervals and Tests of Hypotheses
8.1 Identifying the Target Parameter
8.2 Comparing Two Population Means: Independent Sampling
8.3 Comparing Two Population Means: Paired Difference Experiments
8.4 Comparing Two Population Proportions: Independent Sampling
8.5 Determining the Required Sample Size
8.6 Comparing Two Population Variances: Independent Sampling
Statistics in Action: ZixIt Corp. v. Visa USA Inc.—A Libel Case
Activity 8.1: Box Office Receipts: Comparing Population Means
Activity 8.2: Keep the Change: Inferences Based on Two Samples
Using Technology: TwoSample Inferences
Making Business Decisions: The Kentucky Milk Case—Part II (Covers Chapters 6–8)
9. Design of Experiments and Analysis of Variance
9.1 Elements of a Designed Experiment
9.2 The Completely Randomized Design: Single Factor
9.3 Multiple Comparisons of Means
9.4 The Randomized Block Design
9.5 Factorial Experiments: Two Factors
Statistics in Action: Pollutants at a Housing Development—A Case of Mishandling Small Samples
Activity 9.1: Designed vs. Observational Experiments
Using Technology: Analysis of Variance
10. Categorical Data Analysis
10.1 Categorical Data and the Multinomial Experiment
10.2 Testing Category Probabilities: OneWay Table
10.3 Testing Category Probabilities: TwoWay (Contingency) Table
10.4 A Word of Caution about ChiSquare Tests
Statistics in Action: The Case of the Ghoulish Transplant Tissue—Who Is Responsible for Paying Damages?
Activity 10.1: Binomial vs. Multinomial Experiments
Activity 10.2: Contingency Tables
Using Technology: ChiSquare Analyses
Making Business Decisions: Discrimination in the Workplace (Covers Chapters 9 and 10)
11. Simple Linear Regression
11.1 Probabilistic Models
11.2 Fitting the Model: The Least Squares Approach
11.3 Model Assumptions
11.4 Assessing the Utility of the Model: Making Inferences about the Slope b _{1}
11.5 The Coefficients of Correlation and Determination
11.6 Using the Model for Estimation and Prediction
11.7 A Complete Example
Statistics in Action: Legal Advertising—Does It Pay?
Activity 11.1: Apply Simple Linear Regression to Your Favorite Data
Using Technology: Simple Linear Regression
12. Multiple Regression and Model Building
12.1 Multiple Regression Models
PART I: FirstOrder Models with Quantitative Independent Variables
12.2 Estimating and Making Inferences about the b Parameters
12.3 Evaluating Overall Model Utility
12.4 Using the Model for Estimation and Prediction
PART II: Model Building in Multiple Regression
12.5 Interaction Models
12.6 Quadratic and Other HigherOrder Models
12.7 Qualitative (Dummy) Variable Models
12.8 Models with Both Quantitative and Qualitative Variables
12.9 Comparing Nested Models
12.10 Stepwise Regression
PART III: Multiple Regression Diagnostics
12.11 Residual Analysis: Checking the Regression Assumptions
12.12 Some Pitfalls: Estimability, Multicollinearity, and Extrapolation
Statistics in Action: Bid Rigging in the Highway Construction Industry
Activity 12.1: Insurance Premiums: Collecting Data for Several Variables
Activity 12.2: Collecting Data and Fitting a Multiple Regression Model
Using Technology: Multiple Regression
Making Business Decisions: The Condo Sales Case (Covers Chapters 11 and 12)
13. Methods for Quality Improvement: Statistical Process Control (Available on CD)
13.1 Quality, Processes, and Systems
13.2 Statistical Control
13.3 The Logic of Control Charts
13.4 A Control Chart for Monitoring the Mean of a Process: The [xbar]Chart
13.5 A Control Chart for Monitoring the Variation of a Process: The RChart
13.6 A Control Chart for Monitoring the Proportion of Defectives Generated by a Process: The pChart
13.7 Diagnosing the Causes of Variation
13.8 Capability Analysis
Statistics in Action: Testing Jet Fuel Additive for Safety
Activity 13.1: Quality Control: Consistency
Using Technology: Control Charts
MAKING BUSINESS DECISIONS: The Gasket Manufacturing Case (Covers Chapter 13)
14. Time Series: Descriptive Analyses, Models, and Forecasting (Available on CD)
14.1 Descriptive Analysis: Index Numbers
14.2 Descriptive Analysis: Exponential Smoothing
14.3 Time Series Components
14.4 Forecasting: Exponential Smoothing
14.5 Forecasting Trends: Holt’s Method
14.6 Measuring Forecast Accuracy: MAD and RMSE
14.7 Forecasting Trends: Simple Linear Regression
14.8 Seasonal Regression Models
14.9 Autocorrelation and the DurbinWatson Test
Statistics in Action: Forecasting the Monthly Sales of a New Cold Medicine
Activity 14.1: Time Series
Using Technology: Forecasting
15. Nonparametric Statistics (Available on CD)
15.1 Introduction: DistributionFree Tests
15.2 Single Population Inferences
15.3 Comparing Two Populations: Independent Samples
15.4 Comparing Two Populations: Paired Difference Experiment
15.5 Comparing Three or More Populations: Completely Randomized Design
15.6 Comparing Three or More Populations: Randomized Block Design
15.7 Rank Correlation
Statistics in Action: How Vulnerable Are New Hampshire Wells to Groundwater Contamination?
Activity 15.1: Keep the Change: Nonparametric Statistics
Using Technology: Nonparametric Tests
Making Business Decisions: Detecting “Sales Chasing” (Covers Chapters 10 and 15)
Appendix A: Summation Notation
Appendix B: Basic Counting Rules
Appendix C: Calculation Formulas for Analysis of Variance
C.1 Formulas for the Calculations in the Completely Randomized Design
C.2 Formulas for the Calculations in the Randomized Block Design
C.3 Formulas for the Calculations for a TwoFactor Factorial Experiment
C.4 Tukey's Multiple Comparisons Procedure (Equal Sample Sizes)
C.5 Bonferroni Multiple Comparisons Procedure (Pairwise Comparisons)
C.6 Scheffé's Multiple Comparisons Procedure (Pairwise Comparisons)
Appendix D: Tables
Table I. Binomial Probabilities
Table II. Normal Curve Areas
Table III. Critical Values of t
Table IV. Critical Values of x ^{2}
Table V. Percentage Points of the FDistribution, α = .10
Table VI. Percentage Points of the FDistribution, α = .05
Table VII. Percentage Points of the FDistribution, α = .025
Table VIII. Percentage Points of the FDistribution, α = .01
Table IX. Control Chart Constants
Table X. Critical Values for the DurbinWatson dStatistic, α = .05
Table XI. Critical Values for the DurbinWatson dStatistic, α = .01
Table XII. Critical Values of T_{L} and T_{u} for the Wilcoxon Rank Sum Test: Independent Samples
Table XIII. Critical Values of T0 in the Wilcoxon Paired Difference Signed Rank Test
Table XIV. Critical Values of Spearman's Rank Correlation Coefficient
Table XV. Critical Values of the Studentized Range, α = .05
Answers to Selected Exercises
Index
Credits
Preface
Preface
This eighth edition of Statistics for Business and Economics is an introductory business text emphasizing inference, with extensive coverage of data collection and analysis as needed to evaluate the reported results of statistical studies and to make good decisions. As in earlier editions, the text stresses the development of statistical thinking, the assessment of credibility and value of the inferences made from data, both by those who consume and those who produce them. It assumes a mathematical background of basic algebra.
A briefer version of the book, A First Course in Business Statistics, is available for single semester courses that include minimal coverage of regression analysis, analysis of variance, and categorical data analysis.
NEW IN THE EIGHTH EDITION
Major Content Changes
Chapter 2 includes two new optional sections: methods for detecting outliers (Section 2.8) and graphing bivariate relationships (Section 2.9).
Chapter 5 now covers descriptive methods for assessing whether a data set is approximately normally distributed.
Chapter 11 is a new multiple regression chapter. The material on multiple regression models and model building (Chapters 11 and 12 in previous editions) is reorganized into a single, streamlined chapter, with initial emphasis on the firstorder model. More complex models (e.g., interaction, quadratic, and dummy variable models) are presented in increasing order of difficulty. Coverage of residual analysis (Section 11.13) is expanded to include treatment of heteroscedastic errors.
Exploring DatawithStatistical Computer Software and the Graphing Calculator—Throughout the text, computer printouts from four popular Windowsbased statistical software packages (SAS, SPSS, MINITAB, STATISTIX) are displayed and used to make decisions about the data. New to this edition, we have included instruction boxes and output for the TI83 graphing calculator.
Statistics in Action—One or two features per chapter examine current reallife, highprofile issues. Data from the study is presented for analysis. Questions prompt the students to form their own conclusions and to think through the statistical issues involved.
RealWorld Business Cases—Six extensive business problemsolving cases, with real data and assignments. Each case serves as a good capstone and review of the material that has preceded it.
RealData Exercises—Almost all the exercises in the text employ the use of current real data taken from a wide variety of publications (e.g., newspapers, magazines, and journals).
Quick Review—Each chapter ends with a list of key terms and formulas, with reference to the page number where they first appear.
Language Lab—Following the Quick Review is a pronunciation guide for Greek letters and other special terms. Usage notes are also provided.
TRADITIONAL STRENGTHS
We have maintained the features of Statistics for Business and Economics that we believe make it unique among business statistics texts. These features, which assist the student in achieving an overview of statistics and an understanding of its relevance in the business world and in everyday life, are as follows:
The Use of Examples as a Teaching Device
Almost all new ideas are introduced and illustrated by real databased applications and examples. We believe that students better understand definitions, generalizations, and abstractions after seeing an application.
Many Exercises—Labeled by Type
The text includes more than 1,400 exercises illustrated by applications in almost all areas of research. Because many students have trouble learning the mechanics of statistical techniques when problems are couched in terms of realistic applications, all exercise sections are divided into two parts:
A Choice in Level of Coverage of Probability (Chapter 3)
One of the most troublesome aspects of an introductory statistics course is the study of probability. Probability poses a challenge for instructors because they must decide on the level of presentation, and students find it a difficult subject to comprehend. We believe that one cause for these problems is the mixture of probability and counting rules that occurs in most introductory texts. We have included the counting rules in a separate and optional section at the end of the chapter on probability. In addition, all exercises that require the use of counting rules are marked with an asterisk (*). Thus, the instructor can control the level of coverage of probability.
Extensive Coverage of Multiple Regression Analysis
and Model Building (Chapter 11)
This topic represents one of the most useful statistical tools for the solution of applied problems. Although an entire text could be devoted to regression modeling, we believe we have presented coverage that is understandable, usable, and much more comprehensive than the presentations in other introductory statistics texts.
We devote three chapters to discussing the major types of inferences that can be derived from a regression analysis, showing how these results appear in computer printouts and, most important, selecting multiple regression models to be used in an analysis. Thus, the instructor has the choice of a onechapter coverage of simple regression, a twochapter treatment of simple and multiple regression, or a complete threechapter coverage of simple regression, multiple regression, and model building. This extensive coverage of such useful statistical tools will provide added evidence to the student of the relevance of statistics to the solution of applied problems.
Footnotes
Although the text is designed for students with a noncalculus background, footnotes explain the role of calculus in various derivations. Footnotes are also used to inform the student about some of the theory underlying certain results. The footnotes allow additional flexibility in the mathematical and theoretical level at which the material is presented.
SUPPLEMENTS FOR THE INSTRUCTOR
The supplements for the eighth edition have been completely revised to reflect the revisions of the text. To ensure adherence to the approaches presented in the main text, each element in the package has been accuracy checked for clarity, and freedom from computational, typographical, and statistical errors.
Annotated Instructor's Edition (AIE) (ISBN 0130279854)
Marginal notes placed next to discussions of essential teaching concepts include:
Instructor's Notes by Mark Dummeldinger (ISBN 0130274100)
This printed resource contains suggestions for using the questions at the end of the Statistics in Action boxes as the basis for class discussion on statistical ethics and other current issues, solutions to the RealWorld Cases, a complete short answer book with letter of permission to duplicate for student use, and many of the exercises and solutions that were removed from previous editions of this text.
Instructor's Solutions Manual by Nancy S. Boudreau
(ISBN 0130274216)
Solutions to all of the evennumbered exercises are given in this manual. Careful attention has been paid to ensure that all methods of solution and notation are consistent with those used in the core text. Solutions to the oddnumbered exercises are found in the Student's Solutions Manual.
Test Bank by Mark Dummeldinger (ISBN 0130274194)
Entirely rewritten, the Test Bank now includes more than 1,000 problems that correlate to problems presented in the text.
Test Gen EQ
PowerPoint Presentation Disk by Mark Dummeldinger
(ISBN 0130273651)
This versatile Windowsbased tool may be used by professors in a number of different ways:
Included on the software disk are learning objectives, thinking challenges, concept presentation slides, and examples with workedout solutions. The PowerPoint Presentation Disk may be downloaded from the FTP site found at the McClave Web site.
Data Disk—available free with every text purchased from Prentice Hall
The data sets for all exercises and cases are available on a 3 1/2" diskette in ASCII format in the back of the book. When a given data set is referenced, a disk symbol and the file name will appear in the text near the exercise.
McClave Internet Site (...