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The Basic Practice of Statistics (International Edition) de David S. Moore

The Basic Practice of Statistics (International Edition)

Autor David S. Moore, William I. Notz, Michael A. Fligner
en Limba Engleză Paperback – 29 ian 2021

Recomandăm The Basic Practice of Statistics (International Edition) ca resursă fundamentală pentru studenții de licență, cercetătorii aflați la început de drum și practicienii care au nevoie de o bază solidă în analiza datelor. Această a noua ediție rafinează abordarea pedagogică a autorilor, oferind un parcurs structurat care elimină ambiguitatea din procesul de învățare a metodelor cantitative. Credem că forța acestui volum rezidă în organizarea sa logică: pornește de la explorarea vizuală a distribuțiilor și corelațiilor, trece prin rigoarea producerii datelor prin eșantionare și experimente, și culminează cu mecanismele complexe ale inferenței statistice. Spre deosebire de alte manuale tehnice, The Basic Practice of Statistics (International Edition) integrează un capitol esențial despre etica datelor, o necesitate în peisajul actual al cercetării. Comparabil cu The Practice of Statistics in the Life Sciences în ceea ce privește rigoarea metodologică, acest volum este actualizat pentru a răspunde nevoilor unei audiențe mai largi, nu doar celor din științele vieții, oferind exemple transversale. În contextul operei lui David S. Moore, lucrarea de față reprezintă varianta mai accesibilă a celebrei sale Introduction to the Practice of Statistics. Dacă în lucrări precum The Developing Genome Moore explorează intersecția dintre genetică și mediu, aici el oferă instrumentele matematice necesare pentru a valida orice ipoteză științifică, menținând același standard de claritate care i-a consacrat cariera de profesor.

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Specificații

ISBN-13: 9781319383688
ISBN-10: 1319383688
Pagini: 800
Ilustrații: Bibliographie
Dimensiuni: 213 x 271 x 25 mm
Greutate: 1.46 kg
Ediția:Ninth Edition
Editura: Macmillan Learning
Colecția W. H. Freeman

De ce să citești această carte

Suntem de părere că acest manual este cea mai sigură investiție pentru oricine dorește să înțeleagă statistica fără a se pierde în demonstrații matematice abstracte. Cititorul câștigă capacitatea de a interpreta critic datele, de la grafice simple la teste de semnificație complexe. Este un instrument esențial pentru pregătirea examenelor universitare și pentru fundamentarea oricărui demers de cercetare empirică.

Despre autor

David S. Moore este profesor emerit de psihologie la Pitzer College și Claremont Graduate University, având un doctorat obținut la Harvard University. Experiența sa vastă în psihologia dezvoltării și neuroștiințe cognitive i-a modelat abordarea didactică, punând accent pe claritatea explicațiilor în domenii complexe. Moore este autorul mai multor manuale de succes publicate de W. H. Freeman, fiind recunoscut pentru capacitatea de a face statistica accesibilă. Lucrările sale, precum The Dependent Gene, demonstrează angajamentul său față de rigoarea științifică și demitizarea determinismului, principii care se reflectă și în structura manualelor sale de statistică.

Notă biografică

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 America's 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 Notz's 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 University's 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 Fligners 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 Califo

Cuprins

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

Descriere

Now available with Macmillan's 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.