Statistics: The Exploration and Analysis of Data 7/e (H)
- 20本以上，享 8.5折
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- 一般書籍
- ISBN：9780840058010
- 作者：Jay Devore, Roxy Peck
- 版次：7
- 年份：2012
- 出版商：Cengage Learning
- 頁數/規格：788頁/精裝彩色
- 參考網頁：Statistics: The Exploration and Analysis of Data 7/e
書籍介紹
本書特色
目錄
Description
Roxy Peck and Jay Devore's STATISTICS: THE EXPLORATION AND ANALYSIS OF DATA, 7th Edition uses real data and attention-grabbing examples to introduce students to the study of statistics and data analysis. Traditional in structure yet modern in approach, this text guides students through an intuition-based learning process that stresses interpretation and communication of statistical information. Simple notation--including the frequent substitution of words for symbols--helps students grasp concepts and cement their comprehension. Hands-on activities and interactive applets allow students to practice statistics firsthand.
Roxy Peck and Jay Devore's STATISTICS: THE EXPLORATION AND ANALYSIS OF DATA, 7th Edition uses real data and attention-grabbing examples to introduce students to the study of statistics and data analysis. Traditional in structure yet modern in approach, this text guides students through an intuition-based learning process that stresses interpretation and communication of statistical information. Simple notation--including the frequent substitution of words for symbols--helps students grasp concepts and cement their comprehension. Hands-on activities and interactive applets allow students to practice statistics firsthand.
Features
New to This Edition
- An optional section on logistic regression is included in Chapter 5, "Summarizing Bivariate Data," for those who would like more complete coverage of data analysis techniques for categorical data.
- Advanced topics that are often omitted in a one-quarter or one-semester course, such as inference and variable selection methods in multiple regression and analysis of variance for randomized block and two-factor designs, are available online at the book's website, Statistics CourseMate.
- "Interpreting and Communicating the Results of Statistical Analysis" sections, which emphasize the importance of being able to interpret statistical output and communicate its meaning to non-statisticians, now have assignable end-of-section questions associated with them.
- Real data gives students authentic scenarios that help them understand statistical concepts in relevant, interesting contexts.
- The book features broad coverage of sampling; survey design and experimental design coverage of transformations and nonlinear regression; and an emphasis on graphical display as a necessary component of data analysis.
- The book highlights the role of the computer in contemporary statistics through numerous printouts and exercises that can be solved by computer.
- Several Java™ applets, used in conjunction with activities that appear at the end of the chapter, provide visual insight into statistical concepts.
- A digital image bank and MicrosoftR PowerPointR Slides in the Instructor's Resource Binder make lecture and class preparation quick and easy.
New to This Edition
- New Cumulative Review Exercises appear after selected chapter sets, allowing you to test students' comprehension of topics spanning multiple chapters.
- More than 50 new examples and more than 270 new exercises, which use data from current newspapers and journals, help students understand statistical concepts in a realistic context. In addition, more of the exercises specifically ask students to write (for example, by requiring students to explain their reasoning, interpret results, and comment on important features of an analysis).
- Examples and exercises using data sets that can be accessed online from the text website (Statistics CourseMate) are designated by an icon, as are examples that are further illustrated in technology manuals for MINITABR, SPSSR, etc.--which are also available at the website.
- Exercises have been added to the "Interpreting and Communicating the Results of Statistical Analyses" sections, giving students the chance to practice these important skills. All of these sections now have assignable end-of-section questions associated with them.
- More than 90 exercises have video solutions, presented by Brian Kotz of Montgomery College, which can be viewed online or downloaded for viewing later. An icon designates these exercises in the text.
- A greater number of end-of-chapter activities have been added to the book, ideal for use as a chapter capstone or integrated at appropriate places as the chapter material is covered in class.
- The text is enhanced by a variety of online teaching and learning resources. These include the book's website, Statistics CourseMate; Aplia™, an online interactive learning solution that improves comprehension of key statistical concepts; and Cengage Learning's Enhanced WebAssignR, which allows you to assign problems from the text online and ensure that students receive multimedia tutorial support as they complete their assignments.
Table of Contents
1. THE ROLE OF STATISTICS AND THE DATA ANALYSIS PROCESS.
2. COLLECTING DATA SENSIBLY.
3. GRAPHICAL METHODS FOR DESCRIBING DATA.
4. NUMERICAL METHODS FOR DESCRIBING DATA.
5. SUMMARIZING BIVARIATE DATA.
6. PROBABILITY.
7. RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS.
8. SAMPLING VARIABILITY AND SAMPLING DISTRIBUTION.
9. ESTIMATION USING A SINGLE SAMPLE.
10. HYPOTHESIS TESTING USING A SINGLE SAMPLE.
11. COMPARING TWO POPULATIONS OR TREATMENTS.
12. THE ANALYSIS OF CATEGORICAL DATA AND GOODNESS-OF-FIT TESTS.
13. SIMPLE LINEAR REGRESSION AND CORRELATION: INFERENTIAL METHODS.
14. MULTIPLE REGRESSION ANALYSIS.
15. ANALYSIS OF VARIANCE.
16. NONPARAMETRIC (DISTRIBUTION-FREE STATISTICAL METHODS (ONLINE).
1. THE ROLE OF STATISTICS AND THE DATA ANALYSIS PROCESS.
2. COLLECTING DATA SENSIBLY.
3. GRAPHICAL METHODS FOR DESCRIBING DATA.
4. NUMERICAL METHODS FOR DESCRIBING DATA.
5. SUMMARIZING BIVARIATE DATA.
6. PROBABILITY.
7. RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS.
8. SAMPLING VARIABILITY AND SAMPLING DISTRIBUTION.
9. ESTIMATION USING A SINGLE SAMPLE.
10. HYPOTHESIS TESTING USING A SINGLE SAMPLE.
11. COMPARING TWO POPULATIONS OR TREATMENTS.
12. THE ANALYSIS OF CATEGORICAL DATA AND GOODNESS-OF-FIT TESTS.
13. SIMPLE LINEAR REGRESSION AND CORRELATION: INFERENTIAL METHODS.
14. MULTIPLE REGRESSION ANALYSIS.
15. ANALYSIS OF VARIANCE.
16. NONPARAMETRIC (DISTRIBUTION-FREE STATISTICAL METHODS (ONLINE).
