Mathematical Statistics Problems and Detailed Solutions:Problems and Detailed Solutions. Includes a print and an ebook Ivo B. Alberink/ Wiebe R. Pestman
Learn Statistics Fast: A Simplified Detailed Version for Students: Hesbon R. M
This graduate textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph.D. degree in statistics. This new edition has been revised and updated and in this fourth printing, errors have been ironed out. The first chapter provides a quick overview of concepts and results in measure-theoretic probability theory that are useful in statistics. The second chapter introduces some fundamental concepts in statistical decision theory and inference. Subsequent chapters contain detailed studies on some important topics: unbiased estimation, parametric estimation, nonparametric estimation, hypothesis testing, and confidence sets. A large number of exercises in each chapter provide not only practice problems for students, but also many additional results.
A Primer of Ecological Statistics , Second Edition explains fundamental material in probability theory, experimental design, and parameter estimation for ecologists and environmental scientists. The book emphasizes a general introduction to probability theory and provides a detailed discussion of specific designs and analyses that are typically encountered in ecology and environmental science. Appropriate for use as either a stand-alone or supplementary text for upper-division undergraduate or graduate courses in ecological and environmental statistics, ecology, environmental science, environmental studies, or experimental design, the Primer also serves as a resource for environmental professionals who need to use and interpret statistics daily but have little or no formal training in the subject. The book is divided into four parts. Part I discusses the fundamentals of probability and statistical thinking. It introduces the logic and language of probability (Chapter 1), explains common statistical distributions used in ecology (Chapter 2) and important measures of central tendency and spread (Chapter 3), explains P-values, hypothesis testing, and statistical errors (Chapter 4), and introduces frequentist, Bayesian, and Monte Carlo methods of analysis (Chapter 5). Part II discusses how to successfully design and execute field experiments and sampling studies. Topics include design strategies (Chapter 6), a ´bestiary´ of experimental designs (Chapter 7), and transformations and data management (Chapter 8). Part III discusses specific analyses, and covers the material that is the main core of most statistics texts. Topics include regression (Chapter 9), analysis of variance (Chapter 10), categorical data analysis (Chapter 11), and multivariate analysis (Chapter 12). Part IV-new to this edition-discusses two central topics in estimating important ecological metrics. Topics include quantification of biological diversity (Chapter 13) and estimating occupancy, detection probability, and population sizes from marked and unmarked populations (Chapter 14). The book includes a comprehensive glossary, a mathematical appendix on matrix algebra, and extensively annotated tables and figures. Footnotes introduce advanced and ancillary material: some are purely historical, others cover mathematical/statistical proofs or details, and still others address current topics in the ecological literature. Data files and code used for some of the examples, as well as errata, are available online.
Mathematical Statistics:Problems and Detailed Solutions Wiebe R. Pestman/ Ivo B. Alberink
Statistics and Chemometrics for Analytical Chemistry 7 th edition provides a clear, accessible introduction to main statistical methods used in modern analytical laboratories. It continues to be the ideal companion for students in Chemistry and related fields keen to build their understanding of how to conduct high quality analyses in areas such as the safety of food, water and medicines, environmental monitoring, and chemical manufacturing. With a focus on the underlying statistical ideas, this book incorporates useful real world examples, step by step explanation and helpful exercises throughout. Features of the new edition: · Significant revision of the Quality of analytical measurements chapter to incorporate more detailed coverage of the estimation of measurement uncertainty and the validation of analytical methods. · Updated coverage of a range of topics including robust statistics, Bayesian methods, and testing for normality of distribution, plus expanded material on regression and calibration methods. · Additional experimental design methods, including the increasingly popular optimal designs. · Worked examples have been updated throughout to ensure compatibility with the latest versions of Excel and Minitab. · Exercises are available at the end of each chapter to allow student to check understanding and prepare for exams. Answers are provided at the back of the book for handy reference. This book is aimed at undergraduate and graduate courses in Analytical Chemistry and related topics. It will also be a valuable resource for researchers and chemists working in analytical chemistry.
A crash course in statistics delves into key statistical methods, namely Chi Square, t-test, ANOVA and descriptive statistics. It equally gives an overview of statistical methods as well as various discussions of the statistical tests relating to various database culled from various sources, like the survey of student spending on textbooks, etc. Also, detailed demonstration of various data analysis in SPSS was considered via statistical test. 1. Language: English. Narrator: Andrea Giordani. Audio sample: http://samples.audible.de/bk/acx0/100742/bk_acx0_100742_sample.mp3. Digital audiobook in aax.
Statistics is essential for all business majors, and this text helps students see the role statistics will play in their own careers by providing examples drawn from all functional areas of business. Guided by principles set by major statistical and business science associations (ASA and DSI), plus the authors? diverse experiences, the Seventh Edition of Levine/Szabat/Stephan?s Business Statistics: A First Course continues to innovate and improve the way this course is taught to all students. This brief version, created to fit the needs of a one-semester course, is part of the established Berenson/Levine series. MyStatLab not included. Students, if MyStatLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyStatLab should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information. MyStatLab is an online homework, tutorial, and assessment product designed to personalize learning and improve results. With a wide range of interactive, engaging, and assignable activities, students are encouraged to actively learn and retain tough course concepts. Features + Benefits This title is a Pearson Global Edition. The Editorial team at Pearson has worked closely with educators around the world to include content which is especially relevant to students outside the United States. A real-life business approach grounds the statistics in everyday life, helping students see how the concepts they are learning apply to their future careers. Examples are drawn from key functional areas of business?accounting, finance, information systems, management, and marketing. Up-to-date statistical software instructions and output throughout every chapter familiarize students with how to use these programs in business decision making, and allow them to focus on interpreting data rather than mathematical computations. Using Statistics business scenarios open each chapter, showing how statistics is used in key functional areas of business. These scenarios are used throughout the chapter to provide context for the concepts, culminating in Using Statistics, Revisited, which reinforces the statistical methods and applications discussed in the chapter. Projects-Detailed Case Studies are included in numerous chapters. The Managing Ashland MultiComm Services continuing case, a team project related to bond funds, and undergraduate and graduate student surveys are included at the end of most chapters. They help to integrate learning across the chapters and topics. Digital Cases let students examine interactive PDF documents to sift through various claims and information to discover the conclusions and claims supported by the data. Learners see how to identify common misuses of statistical information. Think About This essays provide greater insight into what students just read and raise important issues about the application of statistical knowledge. Pedagogical tools help keep students on track, providing an ideal framework for learning and understanding the statistical concepts. NEW! Getting Started: Things to Learn First. This new chapter addresses the challenge of students coming to the course with varied statistical backgrounds, sets the context for the course, and ensures that the class starts on the same page. NEW! The revised DCOVA framework (Define, Collect, Organize, Visualize, and Analyze) is used throughout this text as an integrated approach for applying statistics to help solve business problems. Visual Explorations?the Excel add-in workbook allows students to interactively explore important statistical concepts in descriptive statistics, the normal distribution, sampling distributions, and regression analysis. MyStatLab not included. Students, if MyStatLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyStatLab should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information. MyStatLab provides countless opportunities to practice, plus statistics-specific resources and tools that enhance students? experience and comprehension. Exercises with Multimedia Learning Aids: The homework and practice exercises in MyStatLab align with the exercises in the textbook, and they regenerate algorithmically to give students unlimited opportunity for practice and mastery. Exercises offer immediate helpful
Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher.