KEY MESSAGE: The Tenth Edition of this highly-regarded introductory text emphasizes inference and sound decision-making through its extensive coverage of data collection and analysis. McClave develops statistical thinking and teaches readers to properly assess the credibility of inferences-from the vantage point of both the consumer and the producer. This edition incorporates more exercises and more visual features, such as redesigned end-of-chapter summaries and an increased use of applets. This text assumes a mathematical background of basic algebra.
KEY TOPICS: Statistics, Data, and Statistical Thinking; Methods for Describing Sets of Data; Probability (from McClave 11e-Chap 3); Random Variables and Probability Distributions; Inferences Based on a Single Sample: Estimation with Confidence Intervals; Inferences Based on a Single Sample: Tests of Hypothesis; Comparing Population Means; Comparing Population Proportions; Simple Linear Regression
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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 also currently an Adjunct Professor of Statistics at the University of Florida, where he was a full-time member of the faculty for twenty years.
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, as well as advanced statistics to all doctoral candidates, in the College of Business Administration. He has published articles in such journals as the Journal of the American Statistical Association, International Journal of Forecasting, Academy of Management Journal, and the Auditing: A Journal of Practice & Theory. Dr. Sincich is a co-author of the texts Statistics, Statistics for Business & Economics, Statistics for Engineering & the Sciences, and A Second Course in Statistics: Regression Analysis.
This eighth edition of A First Course in Statistics is an introductory text emphasizing inference, with extensive coverage of data collection and analysis as needed to evaluate the reported results of statistical studies and 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. This one-semester text covers basic statistical and probability topics through simple linear regression. It assumes a mathematical background of basic algebra.
NEW TO THE EIGHTH EDITION
Exercise sets have been revised to provide a greater variety in level of difficulty. In addition to "Learning the Mechanics" exercises, "Applied Exercises" are categorized into "Basic," "Intermediate," and "Advanced" at the end of each section.
All printouts from statistical software (SAS, SPSS, MINITAB, and STATISTIX) have been revised to reflect the latest versions of the software.
The sections in Chapter 8 (Comparing Population Proportions) have been reorganized with emphasis on whether one or two qualitative variables are analyzed.
We have maintained the pedagogical features of A First Course in Statistics that we believe make it unique among introductory statistics texts. These features, which assist the student in achieving an overview of statistics and an understanding of its relevance in the social and life sciences, business, and everyday life, are as follows:
Use of Examples as a TeachingDevice. Almost all new ideas are introduced and illustrated by data-based applications and examples. We believe that students better understand definitions, generalizations, and abstractions after seeing an application.
Exploring Data with Statistical Computer Software. Each statistical analysis method presented is demonstrated using output from four leading statistical software packages: SAS, SPSS, MINITAB, or STATISTIX. In addition, output and keystroke instructions for the TI-83 Graphing Calculator are covered in optional boxes.
Nonparametric Methods Integrated. Throughout the text, optional sections on alternative distribution-free (nonparametric) procedures follow the relevant sections.
Statistics in Action. Each chapter concludes with a case study on a contemporary, controversial, or high-profile issue. Data from the study are presented for analysis and questions, prompting the students to evaluate the findings and to think through the statistical issues involved. Additional cases appear on the Web site.
Real Data Exercises. The text includes more than 800 exercises illustrated by applications in almost all areas of research. All the applied exercises employ the use of current real data extracted from a wide variety of publications (e.g., newspapers, magazines, journals, and the Internet). Many students have trouble learning the mechanics of statistical techniques when all problems are couched in terms of realistic applications. For this reason, all exercise sections are divided into four parts:
Learning the Mechanics. Designed as straightforward applications of new concepts, these exercises allow students to test their ability to comprehend a mathematical concept or a definition.
Applying the Concepts—Basic. Based on applications taken from a wide variety of journals, newspapers, and other sources, these short exercises help the student begin developing the skills necessary to diagnose and analyze real-world problems.
Applying the Concepts—Intermediate. Based on more detailed real-world applications, these exercises require students to apply their knowledge of the technique presented in the section.
Applying the Concepts—Advanced. These more challenging real-data exercises require students to utilize their critical thinking skills.
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 to Greek letters and other special terms. Usage notes are also provided.
Student Projects. Presented at the end of each chapter, these projects emphasize gathering data, analyzing data, and/or report writing.
Footnotes. Although the text is designed for students with a non-calculus 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 methods of analysis. These footnotes allow additional flexibility in the mathematical and theoretical level at which the material is presented.