About the Author
Neil A. Weiss received his Ph.D. from UCLA in 1970 and subsequently accepted an assistant-professor position at Arizona State University (ASU), where he was ultimately promoted to the rank of full professor. Dr. Weiss has taught statistics, probability, and mathematics—from the freshman level to the advanced graduate level—for more than 30 years. In recognition of his excellence in teaching, he received the Dean’s Quality Teaching Award from the ASU College of Liberal Arts and Sciences. Dr. Weiss’ comprehensive knowledge and experience ensures that his texts are mathematically and statistically accurate, as well as pedagogically sound.
In addition to his numerous research publications, Dr. Weiss is the author of A Course in Probability (Addison-Wesley, 2006). He has also authored or coauthored books in finite mathematics, statistics, and real analysis, and is currently working on a new book on applied regression analysis and the analysis of variance. His texts—well known for their precision, readability, and pedagogical excellence—are used worldwide.
Dr. Weiss is a pioneer of the integration of statistical software into textbooks and the classroom, first providing such integration over 20 years ago in the book Introductory Statistics (Addison-Wesley, 1982). Weiss and Addison-Wesley continue that pioneering spirit to this day with the inclusion of some of the most comprehensive Web sites in the field.
In his spare time, Dr. Weiss enjoys walking, studying and practicing meditation, and playing hold ’em poker. He is married and has two sons.
Table of Contents
(*indicates an optional section).
Two Kinds of Statistics.
The Technology Center.
Simple Random Sampling.
Other Sampling Designs.
II. DESCRIPTIVE STATISTICS.
Variables and Data.
Graphs and Charts.
Distribution Shapes; Symmetry and Skewness.
3. Descriptive Measures.
Measures of Center.
The Sample Mean.
Measures of Variation; the Sample Standard Deviation.
The Five-Number Summary; Boxplots.
Descriptive Measures for Populations; Use of Samples.
III. PROBABILITY, RANDOM VARIABLES, AND SAMPLING DISTRIBUTIONS.
Some Rules of Probability.
*Contingency Tables; Joint and Marginal Probabilities.
*The Multiplication Rule; Independence.
5. Discrete Random Variables.
*Discrete Random Variables and Probability Distributions.
*The Mean and Standard Deviation of a Discrete Random Variable.
*The Binomial Distribution.
*The Poisson Distribution.
6. The Normal Distribution.
Introducing Normally Distributed Variables.
Areas Under the Standard Normal Curve.
Working With Normally Distributed Variables.
Assessing Normality; Normal Probability Plots.
*Normal Approximation to the Binomial Distribution .
7. The Sampling Distribution of the Sample Mean.
Sampling Error; the Need for Sampling Distributions.
The Mean and Standard Deviation of x.
The Sampling Distribution of the Sample Mean.
IV. INFERENTIAL STATISTICS.
Estimating a Population Mean.
Confidence Intervals for One Population Mean When s Is Known.
Margin of Error.
Confidence Intervals for One Population Mean When s Is Unknown.
9. Hypothesis Tests for One Population Mean.
The Nature of Hypothesis Testing.
Terms, Errors, and Hypotheses.
Hypothesis Tests for One Population Mean When s Is Known.
*Type II Error Probabilities; Power.
Hypothesis Tests for One Population Mean When s Is Unknown.
*The Wilcoxon Signed-Rank Test.
*Which Procedure Should Be Used?
10. Inferences for Two Population Means.
The Sampling Distribution of the Difference Between Two Sample Means for Independent Samples.
Inferences for Two Population Means Using Independent Samples: Standard Deviations Assumed Equal.
Inferences for Two Population Means Using Independent Samples: Standard Deviations Not Assumed Equal.
*The Mann-Whitney Test.
Inferences for Two Population Means Using Paired Samples.
*The Paired Wilcoxon Signed-Rank Test.
*Which Procedure Should Be Used?
11. Inferences for Population Standard Deviations.
*Inferences for One Population Standard Deviation.
*Inferences for Two Population Standard Deviations Using Independent Samples.
12. Inferences for Population Proportions.
Confidence Intervals for One Population Proportion.
Hypothesis Tests for One Population Proportion.
Inferences for Two Population Proportions Using Independent Samples.
13. Chi-Square Procedures.
The Chi-Square Distribution.
Chi-Square Goodness-Of-Fit Test.
Contingency Tables; Association.
Chi-Square Independence Test.
V. REGRESSION, CORRELATION, AND ANOVA.
Linear Equations With One Independent Variable.
The Regression Equation.
The Coefficient of Determination.
15. Inferential Methods in Regression and Correlation.
The Regression Model; Analysis of Residuals.
Inferences for the Slope of the Population Regression Line.
Estimation and Prediction.
Inferences in Correlation.
*Testing for Normality.
16. Analysis of Variance (Anova).
One-Way ANOVA: The Logic.
One-Way ANOVA: The Procedure.
*The Kruskal-Wallis Test.
VI. MULTIPLE REGRESSION AND MODEL BUILDING; EXPERIMENTAL DESIGN AND ANOVA (On Weiss Stats CD).
Estimation of the Regression Parameters.
Inferences Concerning the Utility of the Regression Model.
Inferences Concerning the Utility of Particular Predictor Variables.
Confidence Intervals for Mean Response; Prediction.
Intervals for Response.
Checking Model Assumptions and Residual Analysis.
Module B. Model Building in Regression.
Polynomial Regression Model.
Qualitative Predictor Variables.
Model Selection: Stepwise Regression.
Model Selection: All Subsets Regression.
Pitfalls and Warnings.
Module C. Design Of Experiments and Analysis of Variance.
Two-Way ANOVA: The Logic.
Two-Way ANOVA: The Procedure.
Two-Way ANOVA: Multiple Comparisons.
Randomized Block Designs.
Randomized Block ANOVA: The Logic.
Randomized Block ANOVA: The Procedure.
Randomized Block ANOVA: Multiple Comparisons.
*Friedman's Nonparametric Test for the Randomized Block Design.
Appendix B. Answers To Selected Exercises.
Using and understanding statistics andstatistical procedures have become required skills in virtually everyprofession and academic discipline. The purpose of this book is to helpstudents grasp basic statistical concepts and techniques, and to present real-life opportunities for applying them.
About This Book
The text is intended for a one- or two-semestercourse and for quarter-system courses as well. Instructors can easily fit thetext to the pace and depth they prefer. Introductory high school algebra is asufficient prerequisite. Although mathematically and statistically sound, theapproach doesn't require students to examine complex concepts such asprobability theory and random variables. Students need only understand basicideas such as percentages and histograms.
Advances in technology and newinsights into the practice of teaching statistics have inspired many of thepedagogical strategies used in the Seventh Edition of IntroductoryStatistics,leading to more emphasis on conceptual understanding and less emphasis oncomputation.
Highlights of the Approach
ASA/MAA-GuidelinesCompliant. We followASA/MAA guidelines to stress the interpretation of statistical results, thecontemporary applications of statistics, and the importance of criticalthinking.
Unique Variable-Centered Approach. By consistent and proper use of theterms variable and population, we unified and clarified the various statistical concepts.
Data Analysis and Exploration. We incorporate an extensive amount ofdata analysis and exploration in the text andexercises. Recognizing that notall readers have access to technology, we provide ample opportunity to analyzeand explore data without the use of a computer or statistical calculator.
Detailed and Careful Explanations. We include every step of explanationthat a typical reader might need. Our guiding principle is to avoid cognitivejumps, making the learning process smooth and enjoyable. We believe thatdetailed and careful explanations result in better understanding.
Emphasis on Application. Weconcentrate on the application of statistical techniques to the analysis ofdata. Although statistical theory has been kept to a minimum, we provide athorough explanation of the rationale for the use of each statisticalprocedure.
Parallel Critical-Value/P-Value Approaches. Through aparallel presentation, the book offers complete flexibility in the coverage ofthe critical-value and P-valueapproaches to hypothesis testing-either one or both approaches can be exploredand compared.
ParallelPresentations of Technology.The book offers complete flexibility in the coverage of technology,which includes options for use of Minitab, Excel, and the TI-83/84 Plus. One or more technologies can beexplored and compared.
New and Hallmark Features
Chapter-Opening Features. Included at the beginning of eachchapter is a general description of the chapter, an explanation of how thechapter relates to the text as a whole, and an outline that lists the sectionsin the chapter. Each chapter opens with a classic or contemporary case studythat highlights the real-world relevance of the material. (Case studies arereviewed and discussed at the end of the chapter.) More than one-third of thecase studies are new or updated.
Real-World Examples.Every concept discussed in the text is illustrated by at least onedetailed example. The examples are based on real-life situations and werechosen for their interest level as well as for their illustrative value.
Interpretation Boxes. This feature presents the meaning and significance of statisticalresults in everyday language. Instead of just obtaining the answers or results,students are shown the importance of interpretation.
What Does It Mean?.This feature, found in the margin at appropriate places, states in"plain English" the meaning of definitions, formulas, and key facts. It is alsoused to summarize various expository discussions.
Data Sets. In most examples and many exercises, we present both raw data and summarystatistics. This practice gives a more realistic view of statistics andprovides an opportunity for students to solve problems by computer orstatistical calculator, if so desired. Hundreds of data sets are included, manyof which are new or updated. All data sets, including large ones, are availablein multiple formats on the WeissStats CD.
Procedure Boxes: Why, When, and How. To help students learnstatistical procedures, we developed easy-to-follow, step-by-step methods forcarrying them out. Each step is highlighted and presented again within theillustrating example. This approach shows how the procedure is applied andhelps students master its steps.
The procedure boxes havebeen reformatted to include the "why, when, and how" of the methods. Usually, aprocedure has a brief identifying title followed by a statement of its purpose(why it's used), the assumptions for its use (when it's used), and the stepsfor applying the procedure (how it's used). The procedures have been combinedinto a new, single split format for ease of use and comparison.
The Technology Center.The in-text coverage of statistical technology includes three of themost popular applications: Minitab, Excel, and the TI-83/84 Plus graphingcalculators. We provide instructions and output for the most recent versions ofthese applications, including Release 14 of Minitab. The Technology Centers areintegrated as optional material.
Computer Simulations. Computer simulations appear in both the text and theexercises. The simulations serve as pedagogical aids for understanding complexconcepts such as sampling distributions.
Exercises. Over 1700 exercises provide current,real-world applications and were constructed from an extensive variety ofarticles in newspapers, magazines, statistical abstracts, journals, and Websites; sources are explicitly cited. The exercises help students learn thematerial and, moreover, show that statistics is a lively and relevant discipline.We updated exercises wherever appropriate and have provided many new ones.Exercises related to optional materials are marked with asterisks unless theentire section is optional.
Most section exercise sets are divided intothree categories. Statistical Concepts and Skillsexercises help students master the skills and concepts explicitly discussed inthe section.
Extending the Concepts and Skills exercises invite students to extend their skills byexamining material not necessarily covered in the text. Exercises thatintroduce new concepts are highlighted in blue.
Using Technologyexercises provide students with an opportunity to apply and interpret thecomputing and statistical capabilities of Minitab, Excel, the TI-83/84 Plus,SPSS, or any other statistical technology.
Chapter Reviews. Each chapter review includes chapterobjectives, a list of Key Terms with page references, and a Review Test to help students reviewand study the chapter. Items related to optional materials are marked withasterisks unless the entire chapter is optional.
Award-Winning Internet Projects. Each chapter includes an InternetProject to engage students in active and collaborative learning throughsimulations, demonstrations, and other activities, and guide them throughapplications by using Internet links to access data and other informationprovided by the vast resources of the World Wide Web. The Internet Projects are featured on the Weiss Web site at or call us at 1-888-777-0463.
First, we want to express our sincereappreciation to all reviewers of previous editions for their many contributionsto the evolution of the book. For this and the previous few editions of thebook, it is our pleasure to thank the following reviewers, whose comments andsuggestions resulted in significant improvements.
Bowling Green StateUniversity
Pima Community College
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Louisiana Tech University
Raritan Valley CommunityCollege
Holy Cross College
University of Northern Iowa
Sonoma State University
The College of New Jersey
University of Pittsburgh
Western Illinois University
Ennis Donice McCune
Stephen F. Austin StateUniversity
Jacqueline B. Miller
Bernard J. Morzuch
University of Massachusetts,Amherst
Dennis M. O'Brien
University of Wisconsin, LaCrosse
Dwight M. Olson
John Carroll University
Valencia Community College
Northern Illinois University
Cathy D. Poliak
Northern Illinois University
Kimberley A. Polly
California State University
B. Madhu Rao
Bowling Green StateUniversity
Gina F. Reed
Steven E. Rigdon
Southern Illinois University,Edwardsville
Georgia Perimeter College
University of Michigan
George W. Schultz
St. Petersburg Jr. College
University of South Alabama
University of Kentucky,Lexington
W. Ed Stephens
McNeese State University
Clackamas Community College
Valencia Community College
Georgia Institute ofTechnology
California State University,Bakersfield
University of Missouri,Columbia