Principles Statistics And Applications

Author : Ray M. Merrill
Publisher : Jones & Bartlett Learning
Page : 385 pages
File Size : 43,7 Mb
Release : 2021-09-03
Category : Education
ISBN : 9781284225976

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Principles and Applications of Biostatistics by Ray M. Merrill Pdf

Principles and Applications of Biostatistics covers the primary concepts and methods that are required for a fundamental understanding of the use and interpretation of statistics for the biological and health sciences–from data presentation to multiple regression and analysis of variance. With a focus clarity, brevity, and accuracy, this text provides understandable and focused explanation of statistical principles and applications along with practical examples (provided in R and Microsoft Excel) and problems drawn from biological health and medical settings. Key Features: • Practical questions follow each problem to encourage students to consider why the problem likely exists, help formulate hypotheses, and then statistically assess those hypotheses. • Abundant assignment problems at the end of sections and each chapter cover a variety of application areas of biostatistics. • Rationale boxes offer explanations of why certain methods are used for specific cases.

Author : William J. Adams,Irwin Kabus,Mitchell P. Preiss
Publisher : Xlibris Corporation
Page : 756 pages
File Size : 47,8 Mb
Release : 2009-02-03
Category : Mathematics
ISBN : 9781469107318

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Statistics by William J. Adams,Irwin Kabus,Mitchell P. Preiss Pdf

" Our objective in this book is to present an exposition of basic principles of statistics along with some indication of applications which satisfies the following ten commandments: The focus should be placed on a clear development of basic ideas and principles. The exposition of these basic ideas and principles should be streamlined so as to avoid having the undergrowth get in the way of the statistical forest. High priority should be given to the assumptions which underlie the application of statistical principles. Understanding of abuses, misuses, and misunderstandings which have arisen from the application of statistics is essential for a correct understanding of statistics. The coverage should provide students with sufficient preparation for continued study of intermediate and advanced level statistics or disciplines which use statistical methodology. The exposition should be readable and understandable by students without sacrifice of mathematical accuracy. The organization should clearly distinguish mainstream topics inherent in every basic level statistics course, irrespective of applied interests, from topics of special interest to particular audience segments. The computation dimension should not be given equal billing with statistical principles and ideas. Statistics is the master and, important as it is, the computation tool is the servant. Exercises to provoke-thought - exercise the little grey cells, as Hercule Poirot would put it - should be a prominent part of the exposition. Exercise banks to help the student see statistics as a whole are important.

Author : William J. Adams,Irwin Kabus,Mitchell P. Preiss
Publisher : Kendall/Hunt Publishing Company
Page : 144 pages
File Size : 54,5 Mb
Release : 1994-03-01
Category : Statistics
ISBN : 0840394144

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Companion to Statistics by William J. Adams,Irwin Kabus,Mitchell P. Preiss Pdf

Author : R. Mead,S. G. Gilmour,A. Mead
Publisher : Cambridge University Press
Page : 587 pages
File Size : 55,5 Mb
Release : 2012-09-13
Category : Mathematics
ISBN : 9781139576642

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Statistical Principles for the Design of Experiments by R. Mead,S. G. Gilmour,A. Mead Pdf

This book is about the statistical principles behind the design of effective experiments and focuses on the practical needs of applied statisticians and experimenters engaged in design, implementation and analysis. Emphasising the logical principles of statistical design, rather than mathematical calculation, the authors demonstrate how all available information can be used to extract the clearest answers to many questions. The principles are illustrated with a wide range of examples drawn from real experiments in medicine, industry, agriculture and many experimental disciplines. Numerous exercises are given to help the reader practise techniques and to appreciate the difference that good design can make to an experimental research project. Based on Roger Mead's excellent Design of Experiments, this new edition is thoroughly revised and updated to include modern methods relevant to applications in industry, engineering and modern biology. It also contains seven new chapters on contemporary topics, including restricted randomisation and fractional replication.

Author : S. James Press
Publisher : Unknown
Page : 264 pages
File Size : 45,6 Mb
Release : 1989-05-10
Category : Mathematics
ISBN : UOM:39015015723250

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Bayesian Statistics by S. James Press Pdf

An introduction to Bayesian statistics, with emphasis on interpretation of theory, and application of Bayesian ideas to practical problems. First part covers basic issues and principles, such as subjective probability, Bayesian inference and decision making, the likelihood principle, predictivism, and numerical methods of approximating posterior distributions, and includes a listing of Bayesian computer programs. Second part is devoted to models and applications, including univariate and multivariate regression models, the general linear model, Bayesian classification and discrimination, and a case study of how disputed authorship of some of the Federalist Papers was resolved via Bayesian analysis. Includes biographical material on Thomas Bayes, and a reproduction of Bayes's original essay. Contains exercises.

Author : Roberto Rivera
Publisher : John Wiley & Sons
Page : 688 pages
File Size : 48,8 Mb
Release : 2020-02-05
Category : Mathematics
ISBN : 9781119486411

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Principles of Managerial Statistics and Data Science by Roberto Rivera Pdf

Introduces readers to the principles of managerial statistics and data science, with an emphasis on statistical literacy of business students Through a statistical perspective, this book introduces readers to the topic of data science, including Big Data, data analytics, and data wrangling. Chapters include multiple examples showing the application of the theoretical aspects presented. It features practice problems designed to ensure that readers understand the concepts and can apply them using real data. Over 100 open data sets used for examples and problems come from regions throughout the world, allowing the instructor to adapt the application to local data with which students can identify. Applications with these data sets include: Assessing if searches during a police stop in San Diego are dependent on driver’s race Visualizing the association between fat percentage and moisture percentage in Canadian cheese Modeling taxi fares in Chicago using data from millions of rides Analyzing mean sales per unit of legal marijuana products in Washington state Topics covered in Principles of Managerial Statistics and Data Science include:data visualization; descriptive measures; probability; probability distributions; mathematical expectation; confidence intervals; and hypothesis testing. Analysis of variance; simple linear regression; and multiple linear regression are also included. In addition, the book offers contingency tables, Chi-square tests, non-parametric methods, and time series methods. The textbook: Includes academic material usually covered in introductory Statistics courses, but with a data science twist, and less emphasis in the theory Relies on Minitab to present how to perform tasks with a computer Presents and motivates use of data that comes from open portals Focuses on developing an intuition on how the procedures work Exposes readers to the potential in Big Data and current failures of its use Supplementary material includes: a companion website that houses PowerPoint slides; an Instructor's Manual with tips, a syllabus model, and project ideas; R code to reproduce examples and case studies; and information about the open portal data Features an appendix with solutions to some practice problems Principles of Managerial Statistics and Data Science is a textbook for undergraduate and graduate students taking managerial Statistics courses, and a reference book for working business professionals.

Author : William J. Adams
Publisher : Xlibris Corporation
Page : 756 pages
File Size : 41,9 Mb
Release : 2009-02
Category : Mathematics
ISBN : 1436301807

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Statistics by William J. Adams Pdf

" Our objective in this book is to present an exposition of basic principles of statistics along with some indication of applications which satisfies the following ten commandments: The focus should be placed on a clear development of basic ideas and principles. The exposition of these basic ideas and principles should be streamlined so as to avoid having the undergrowth get in the way of the statistical forest. High priority should be given to the assumptions which underlie the application of statistical principles. Understanding of abuses, misuses, and misunderstandings which have arisen from the application of statistics is essential for a correct understanding of statistics. The coverage should provide students with sufficient preparation for continued study of intermediate and advanced level statistics or disciplines which use statistical methodology. The exposition should be readable and understandable by students without sacrifice of mathematical accuracy. The organization should clearly distinguish mainstream topics inherent in every basic level statistics course, irrespective of applied interests, from topics of special interest to particular audience segments. The computation dimension should not be given equal billing with statistical principles and ideas. Statistics is the master and, important as it is, the computation tool is the servant. Exercises to provoke-thought - exercise the little grey cells, as Hercule Poirot would put it - should be a prominent part of the exposition. Exercise banks to help the student see statistics as a whole are important.

Author : D. R. Cox,Christl A. Donnelly
Publisher : Cambridge University Press
Page : 213 pages
File Size : 45,9 Mb
Release : 2011-07-28
Category : Mathematics
ISBN : 9781139503549

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Principles of Applied Statistics by D. R. Cox,Christl A. Donnelly Pdf

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 interpretation, and finally to meaningful conclusions, this book will be a valuable guide. Over a hundred illustrations from a wide variety of real applications make the conceptual points concrete, illuminating your path and deepening your understanding. This book is essential reading for anyone who makes extensive use of statistical methods in their work.

Author : Narayanaswamy Balakrishnan
Publisher : John Wiley & Sons
Page : 937 pages
File Size : 51,9 Mb
Release : 2014-03-05
Category : Medical
ISBN : 9781118595916

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Methods and Applications of Statistics in Clinical Trials, Volume 1 by Narayanaswamy Balakrishnan Pdf

A complete guide to the key statistical concepts essential for the design and construction of clinical trials As the newest major resource in the field of medical research, Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs presents a timely and authoritative reviewof the central statistical concepts used to build clinical trials that obtain the best results. The referenceunveils modern approaches vital to understanding, creating, and evaluating data obtained throughoutthe various stages of clinical trial design and analysis. Accessible and comprehensive, the first volume in a two-part set includes newly-written articles as well as established literature from the Wiley Encyclopedia of Clinical Trials. Illustrating a variety of statistical concepts and principles such as longitudinal data, missing data, covariates, biased-coin randomization, repeated measurements, and simple randomization, the book also provides in-depth coverage of the various trial designs found within phase I-IV trials. Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs also features: Detailed chapters on the type of trial designs, such as adaptive, crossover, group-randomized, multicenter, non-inferiority, non-randomized, open-labeled, preference, prevention, and superiority trials Over 100 contributions from leading academics, researchers, and practitioners An exploration of ongoing, cutting-edge clinical trials on early cancer and heart disease, mother-to-child human immunodeficiency virus transmission trials, and the AIDS Clinical Trials Group Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs is an excellent reference for researchers, practitioners, and students in the fields of clinicaltrials, pharmaceutics, biostatistics, medical research design, biology, biomedicine, epidemiology,and public health.

Author : L. Eriksson,T. Byrne,E. Johansson,J. Trygg,C. Vikström
Publisher : Umetrics Academy
Page : 509 pages
File Size : 40,6 Mb
Release : 2013-07-01
Category : Mathematics
ISBN : 9789197373050

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Multi- and Megavariate Data Analysis Basic Principles and Applications by L. Eriksson,T. Byrne,E. Johansson,J. Trygg,C. Vikström Pdf

To understand the world around us, as well as ourselves, we need to measure many things, many variables, many properties of the systems and processes we investigate. Hence, data collected in science, technology, and almost everywhere else are multivariate, a data table with multiple variables measured on multiple observations (cases, samples, items, process time points, experiments). This book describes a remarkably simple minimalistic and practical approach to the analysis of data tables (multivariate data). The approach is based on projection methods, which are PCA (principal components analysis), and PLS (projection to latent structures) and the book shows how this works in science and technology for a wide variety of applications. In particular, it is shown how the great information content in well collected multivariate data can be expressed in terms of simple but illuminating plots, facilitating the understanding and interpretation of the data. The projection approach applies to a variety of data-analytical objectives, i.e., (i) summarizing and visualizing a data set, (ii) multivariate classification and discriminant analysis, and (iii) finding quantitative relationships among the variables. This works with any shape of data table, with many or few variables (columns), many or few observations (rows), and complete or incomplete data tables (missing data). In particular, projections handle data matrices with more variables than observations very well, and the data can be noisy and highly collinear. Authors: The five authors are all connected to the Umetrics company (www.umetrics.com) which has developed and sold software for multivariate analysis since 1987, as well as supports customers with training and consultations. Umetrics' customers include most large and medium sized companies in the pharmaceutical, biopharm, chemical, and semiconductor sectors.

Author : R. Mead
Publisher : Cambridge University Press
Page : 640 pages
File Size : 41,8 Mb
Release : 1990-07-26
Category : Mathematics
ISBN : 0521287626

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The Design of Experiments by R. Mead Pdf

In all the experimental sciences, good design of experiments is crucial to the success of research. Well-planned experiments can provide a great deal of information efficiently and can be used to test several hypotheses simultaneously. This book is about the statistical principles of good experimental design and is intended for all applied statisticians and practising scientists engaged in the design, implementation and analysis of experiments. Professor Mead has written the book with the emphasis on the logical principles of statistical design and employs a minimum of mathematics. Throughout he assumes that the large-scale analysis of data will be performed by computers and he is thus able to devote more attention to discussions of how all of the available information can be used to extract the clearest answers to many questions. The principles are illustrated with a wide range of examples drawn from medicine, agriculture, industry and other disciplines. Numerous exercises are given to help the reader practise techniques and to appreciate the difference that good design of experiments can make to a scientific project.

Author : Valeriy Skorokhod
Publisher : Springer Science & Business Media
Page : 282 pages
File Size : 46,7 Mb
Release : 2005-12-05
Category : Mathematics
ISBN : 9783540263128

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Basic Principles and Applications of Probability Theory by Valeriy Skorokhod Pdf

The book is an introduction to modern probability theory written by one of the famous experts in this area. Readers will learn about the basic concepts of probability and its applications, preparing them for more advanced and specialized works.

Author : D. R. Cox
Publisher : Cambridge University Press
Page : 227 pages
File Size : 51,5 Mb
Release : 2006-08-10
Category : Mathematics
ISBN : 9781139459136

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Principles of Statistical Inference by D. R. Cox Pdf

In this definitive book, D. R. Cox gives a comprehensive and balanced appraisal of statistical inference. He develops the key concepts, describing and comparing the main ideas and controversies over foundational issues that have been keenly argued for more than two-hundred years. Continuing a sixty-year career of major contributions to statistical thought, no one is better placed to give this much-needed account of the field. An appendix gives a more personal assessment of the merits of different ideas. The content ranges from the traditional to the contemporary. While specific applications are not treated, the book is strongly motivated by applications across the sciences and associated technologies. The mathematics is kept as elementary as feasible, though previous knowledge of statistics is assumed. The book will be valued by every user or student of statistics who is serious about understanding the uncertainty inherent in conclusions from statistical analyses.

Author : Janet Susan Milton,Jesse C. Arnold
Publisher : Unknown
Page : 798 pages
File Size : 41,6 Mb
Release : 2002-11-01
Category : Computer science
ISBN : 0071242481

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Introduction to Probability and Statistics by Janet Susan Milton,Jesse C. Arnold Pdf

This well-respected text is designed for the first course in probability and statistics taken by students majoring in Engineering and the Computing Sciences. The prerequisite is one year of calculus. The text offers a balanced presentation of applications and theory. The authors take care to develop the theoretical foundations for the statistical methods presented at a level that is accessible to students with only a calculus background. They explore the practical implications of the formal results to problem-solving so students gain an understanding of the logic behind the techniques as well as practice in using them. The examples, exercises, and applications were chosen specifically for students in engineering and computer science and include opportunities for real data analysis.

Author : Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani,Jonathan Taylor
Publisher : Springer Nature
Page : 617 pages
File Size : 46,7 Mb
Release : 2023-08-01
Category : Mathematics
ISBN : 9783031387470

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An Introduction to Statistical Learning by Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani,Jonathan Taylor Pdf

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.