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E-raamat: Basic Practice of Statistics

  • Formaat: 772 pages
  • Ilmumisaeg: 26-Apr-2021
  • Kirjastus: W.H.Freeman & Co Ltd
  • Keel: eng
  • ISBN-13: 9781319383695
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  • Formaat: 772 pages
  • Ilmumisaeg: 26-Apr-2021
  • Kirjastus: W.H.Freeman & Co Ltd
  • Keel: eng
  • ISBN-13: 9781319383695
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Now available with Macmillans new online learning tool Achieve, the ninth edition of The Basic Practice of Statistics 9e teaches statistical thinking by guiding students through an investigative process of problem-solving with pedagogy designed to help students of all levels. Examples and exercises from a wide variety of topic areas use current, real data to provide students insight into how and why statistics are used to make decisions in the real world. Achieve for The Basic Practice of Statistics connects the trusted Four-Step problem-solving approach and real world examples in the book to rich digital resources that foster further understanding and application of statistics. Assets in Achieve support learning before, during, and after class for students, while providing instructors with class performance analytics in an easy-to-use interface. Achieve Online Homework Macmillans new online learning tool Achieve features intuitive design, assessment, insights, and reporting built with the direct input of students, educators, and our learning science team. Achieve for The Basic Practice of Statistics features: Learning Objectives tagged to all assessments within Achieve. In-Class Activity Guides to facilitate active learning during class time. over 3,000 homework questions, each with hints, answer-specific feedback, and a fully worked solution. LearningCurve adaptive quizzing. an interactive e-book, powered by VitalSource. multimedia student resources, such as interactive applets and videos. data sets for common statistical software, video technology manuals, and access to Macmillans proprietary statistical software, CrunchIt! Content Updates to the Ninth Edition: Examples and exercises more clearly emphasize the decision-making process. Chapter Summaries and Review Chapters have been revised to help students check their knowledge and review for exams. - Summaries are in concise list form, and Skills Reviews (in Review Chapters) refer back to relevant chapter sections. Data in examples and exercises have been updated for currency, and new examples and exercises explore contemporary issues such as social media usage.
Chapter 0 Getting Started Part I: Exploring Data
Chapter 1 Picturing
Distributions with Graphs
Chapter 2 Describing Distributions with Numbers
Chapter 3 The Normal Distributions
Chapter 4 Scatterplots and Correlation
Chapter 5 Regression
Chapter 6 Two-Way Tables
Chapter 7 Exploring Data: Part
I Review Part II: Producing Data
Chapter 8 Producing Data: Sampling
Chapter 9
Producing Data: Experiments
Chapter 10 Data Ethics
Chapter 11 Producing Data:
Part II Review Part III: From Data Production to Inference
Chapter 12
Introducing Probability
Chapter 13 General Rules of Probability
Chapter 14
Binomial Distributions
Chapter 15 Sampling Distributions
Chapter 16
Confidence Intervals: The Basics
Chapter 17 Tests of Significance: The Basics
Chapter 18 Inference in Practice
Chapter 19 From Data Production to
Inference: Part III Review Part IV: Inference about Variables
Chapter 20
Inference about a Population Mean
Chapter 21 Comparing Two Means
Chapter 22
Inference about a Population Proportion
Chapter 23 Comparing Two Proportions
Chapter 24 Inference about Variables: Part IV Review
Chapter 25 Categorical
Variables: The Chi-Square Test
Chapter 26 Inference for Regression
Chapter 27
One-Way Analysis of Variance: Comparing Several Means Part VI: Optional
Companion
Chapters Available Online
Chapter 28 Nonparametric Tests
Chapter 29
Multiple Regression
Chapter 30 Two-Way Analysis of Variance
Chapter 31
Statistical Process Control
Chapter 32 Resampling: Permutation Tests and the
Bootstrap
David S. Moore is Shanti S. Gupta Distinguished Professor of Statistics, Emeritus, at Purdue University and was 1998 president of the American Statistical Association. He received his AB from Princeton and his PhD from Cornell, both in mathematics. He has written many research papers in statistical theory and served on the editorial boards of several major journals. Professor Moore is an elected fellow of the American Statistical Association and of the Institute of Mathematical Statistics and an elected member of the International Statistical Institute. He has served as program director for statistics and probability at the National Science Foundation. In recent years, Professor Moore has devoted his attention to the teaching of statistics. He was the content developer for the Annenberg/Corporation for Public Broadcasting college-level telecourse Against All Odds: Inside Statistics and for the series of video modules Statistics: Decisions through Data, intended to aid the teaching of statistics in schools. He is the author of influential articles on statistics education and of several leading texts. Professor Moore has served as president of the International Association for Statistical Education and has received the Mathematical Association of Americas national award for distinguished college or university teaching of mathematics. William I. Notz is Professor of Statistics at the Ohio State University. He received his B.S. in physics from the Johns Hopkins University and his Ph.D. in mathematics from Cornell University. His first academic job was as an assistant professor in the Department of Statistics at Purdue University. While there, he taught the introductory concepts course with Professor Moore and as a result of this experience he developed an interest in statistical education. Professor Notz is a co-author of EESEE (the Electronic Encyclopedia of Statistical Examples and Exercises) and co-author of Statistics: Concepts and Controversies. Professor Notzs research interests have focused on experimental design and computer experiments. He is the author of several research papers and of a book on the design and analysis of computer experiments. He is an elected fellow of the American Statistical Association. He has served as the editor of the journal Technometrics and as editor of the Journal of Statistics Education. He has served as the Director of the Statistical Consulting Service, as acting chair of the Department of Statistics for a year, and as an Associate Dean in the College of Mathematical and Physical Sciences at the Ohio State University. He is a winner of the Ohio State Universitys Alumni Distinguished Teaching Award. Michael A. Fligner is an Adjunct Professor at the University of California at Santa Cruz and a non-resident Professor Emeritus with the Ohio State University. He received his B.S. in mathematics from the State University of New York at Stony Brook and his Ph.D. from the University of Connecticut. He spent almost 40 years at the Ohio State University where he was Vice Chair of the Department for over 10 years and also served as Director of the Statistical Consulting Service. He has done consulting work with several large corporations in Central Ohio. Professor Fligner's research interests are in Nonparametric Statistical methods and he received the Statistics in Chemistry award from the American Statistical Association for work on detecting biologically active compounds. He is co-author of the book Statistical Methods for Behavioral Ecology and received a Fulbright scholarship under the American Republics Research program to work at the Charles Darwin Research Station in the Galapagos Islands. He has been an Associate Editor of the Journal of Statistical Education. Professor Fligner is currently associated with the Center for Statistical Analysis in the Social Sciences at the University of California at Santa Cruz.