• формат djvu
  • размер 7.12 МБ
  • добавлен 25 августа 2011 г.
Rice J.A. Mathematical Statistics and Data Analysis
Duxbury Prеss, 1994. - 672 pages.

This is the first text in a generation to re-examine the purpose of the mathematical statistics course. The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statistics. The author stresses analysis of data, examines real problems with real data, and motivates the theory. The book's descriptive statistics, graphical displays, and realistic applications stand in strong contrast to traditional texts which are set in abstract settings.
Похожие разделы
Смотрите также

Cox D.R., Donnelly C.A. Principles of Applied Statistics

  • формат pdf
  • размер 1.08 МБ
  • добавлен 22 января 2012 г.
Cambridge University Press, 2011. - 202 p. - Applied statistics is more than data analysis, but it is easy to lose sight of the big picture. David Cox and Christl Donnelly distil decades of scientific experience into usable principles for the successful application of statistics, showing how good statistical strategy shapes every stage of an investigation. As you advance from research or policy question, to study design, through modelling and int...

Davison A.C. Statistical Models

  • формат pdf
  • размер 5.05 МБ
  • добавлен 15 октября 2011 г.
Cambridge University Press, 2008. - 738 pages. Models and likelihood are the backbone of modern statistics and data analysis. The coverage is unrivaled, with sections on survival analysis, missing data, Markov chains, Markov random fields, point processes, graphical models, simulation and Markov chain Monte Carlo, estimating functions, asymptotic approximations, local likelihood and spline regressions as well as on more standard topics. Anthony...

Devore J.L., Berk K.N. Modern Mathematical Statistics with Applications

  • формат pdf
  • размер 5.44 МБ
  • добавлен 06 сентября 2011 г.
Thompson, 2006. - 848 pages. Many mathematical statistics texts are heavily oriented toward a rigorous mathematical development of probability and statistics, without emphasizing contemporary statistical practice. "Modern Mathematical Statistics with Applications" strikes a balance between mathematical foundations and statistical practice. Accomplished authors Jay Devore and Ken Berk first engage students with real-life problems and scenarios an...

Devore J.L., Berk K.N. Modern Mathematical Statistics with Applications

  • формат pdf
  • размер 13.65 МБ
  • добавлен 21 декабря 2011 г.
Springer, 2011. - 857 pages. Many mathematical statistics texts are heavily oriented toward a rigorous mathematical development of probability and statistics, without much attention paid to how statistics is actually used. In contrast, Modern Mathematical Statistics with Applications, Second Edition strikes a balance between mathematical foundations and statistical practice. In keeping with the recommendation that every math student should stud...

Gamiz M.L. et al Applied Nonparametric Statistics in Reliability

  • формат pdf
  • размер 2.04 МБ
  • добавлен 08 января 2012 г.
Publisher: Springer | 2011 | ISBN10: 0857291173 | 230 pages Nonparametric statistics has probably become the leading methodology for researchers performing data analysis. It is nevertheless true that, whereas these methods have already proved highly effective in other applied areas of knowledge such as biostatistics or social sciences, nonparametric analyses in reliability currently form an interesting area of study that has not yet been fully ex...

Jun Shao. Mathematical Statistics

  • формат pdf
  • размер 32.38 МБ
  • добавлен 21 ноября 2011 г.
Springer, 530 pages, 1999. This book consists of four hundred exercises in mathematical statistics and their solutions. This book is for students preparing for work on a Ph.D. degree in statistics and instructors of mathematical statistics courses, this useful book provides solutions to train students for their research ability in mathematical statistics and presents many additional results and examples that complement any text in mathematical st...

Larsen R.J., Marx M.L. Introduction to Mathematical Statistics and Its Applications

  • формат djvu
  • размер 13.25 МБ
  • добавлен 11 декабря 2010 г.
Prentice Hall, 2005. - 928 pages. Noted for its integration of real-world data and case studies, this guide offers sound coverage of the theoretical aspects of mathematical statistics. It demonstrates how and when to use statistical methods, while reinforcing the calculus that readers have already mastered. Presents standard statistical techniques in a mathematical context, allowing the reader to see the underlying hypotheses for the application...

Lewicki P., Hill T. Statistics: Methods and Applications

  • формат pdf
  • размер 6.03 МБ
  • добавлен 28 октября 2010 г.
Книга Левицки и Хилла по методам и применению статистики (719 страниц) основана на университетских курсах по статистике, состоит из 42 частей; она охватывает очень широкий круг применения, включая лабораторные исследования, бизнес-статистику и прогноз, социальную статистику и исследования методом опроса, сбор данных, инженерию и контроль качества, а также множество других сфер. This book offers training in the understanding and application of st...

Ott R.L., Longnecker M.T. An Introduction to Statistical Methods and Data Analysis

  • формат pdf
  • размер 19.03 МБ
  • добавлен 09 января 2011 г.
Название: An Introduction to Statistical Methods and Data Analysis. Издательство: Brooks/Cole. Автор: R. Lyman Ott, Micheal T. Longnecker. Год: 2010. Количество страниц: 1296. Язык: English. Ott and Longnecker's AN INTRODUCTION TO STATISTICAL METHODS AND DATA ANALYSIS, Sixth Edition, provides a broad overview of statistical methods for readers who have little or no prior experience in statistics. The authors teach readers to solve problems encoun...

Terrell G. Mathematical Statistics: A Unified Introduction

  • формат pdf
  • размер 2.36 МБ
  • добавлен 06 августа 2011 г.
Springer, 1999. - 453 pages. This textbook introduces the mathematical concepts and methods that underlie statistics. The course is unified, in the sense that no prior knowledge of probability theory is assumed; this is developed as needed. The book is committed to a high level of mathematical seriousness; and to an intimate connection with application. Modern methods, such as logistic regression, are introduced; as are unjustly neglected class...