Book Description
Even with a limited mathematics background, readers can understand what statistical methods are & how they may be used to obtain the best possible results from experimental measurements & data.
Author : Hugh D. Young
Publisher :
Page : 196 pages
File Size : 42,63 MB
Release : 1996-08
Category : Mathematics
ISBN :
Even with a limited mathematics background, readers can understand what statistical methods are & how they may be used to obtain the best possible results from experimental measurements & data.
Author : John Mandel
Publisher : Courier Corporation
Page : 434 pages
File Size : 42,81 MB
Release : 2012-06-08
Category : Mathematics
ISBN : 048613959X
First half of book presents fundamental mathematical definitions, concepts, and facts while remaining half deals with statistics primarily as an interpretive tool. Well-written text, numerous worked examples with step-by-step presentation. Includes 116 tables.
Author : Hugh David Young
Publisher :
Page : 0 pages
File Size : 35,13 MB
Release : 1995
Category :
ISBN : 9780070726468
Author : John Robert Green
Publisher :
Page : 382 pages
File Size : 19,57 MB
Release : 1978
Category :
ISBN :
Author : John Robert Green
Publisher :
Page : 0 pages
File Size : 37,95 MB
Release : 1978
Category :
ISBN : 9780444416896
Author : Robert G. Easterling
Publisher : John Wiley & Sons
Page : 268 pages
File Size : 36,1 MB
Release : 2015-09-08
Category : Mathematics
ISBN : 1118954637
Professionals in all areas – business; government; the physical, life, and social sciences; engineering; medicine, etc. – benefit from using statistical experimental design to better understand their worlds and then use that understanding to improve the products, processes, and programs they are responsible for. This book aims to provide the practitioners of tomorrow with a memorable, easy to read, engaging guide to statistics and experimental design. This book uses examples, drawn from a variety of established texts, and embeds them in a business or scientific context, seasoned with a dash of humor, to emphasize the issues and ideas that led to the experiment and the what-do-we-do-next? steps after the experiment. Graphical data displays are emphasized as means of discovery and communication and formulas are minimized, with a focus on interpreting the results that software produce. The role of subject-matter knowledge, and passion, is also illustrated. The examples do not require specialized knowledge, and the lessons they contain are transferrable to other contexts. Fundamentals of Statistical Experimental Design and Analysis introduces the basic elements of an experimental design, and the basic concepts underlying statistical analyses. Subsequent chapters address the following families of experimental designs: Completely Randomized designs, with single or multiple treatment factors, quantitative or qualitative Randomized Block designs Latin Square designs Split-Unit designs Repeated Measures designs Robust designs Optimal designs Written in an accessible, student-friendly style, this book is suitable for a general audience and particularly for those professionals seeking to improve and apply their understanding of experimental design.
Author : Jimmie Leppink
Publisher : Springer
Page : 301 pages
File Size : 50,91 MB
Release : 2019-05-30
Category : Education
ISBN : 3030212416
This book focuses on experimental research in two disciplines that have a lot of common ground in terms of theory, experimental designs used, and methods for the analysis of experimental research data: education and psychology. Although the methods covered in this book are also frequently used in many other disciplines, including sociology and medicine, the examples in this book come from contemporary research topics in education and psychology. Various statistical packages, commercial and zero-cost Open Source ones, are used. The goal of this book is neither to cover all possible statistical methods out there nor to focus on a particular statistical software package. There are many excellent statistics textbooks on the market that present both basic and advanced concepts at an introductory level and/or provide a very detailed overview of options in a particular statistical software programme. This is not yet another book in that genre. Core theme of this book is a heuristic called the question-design-analysis bridge: there is a bridge connecting research questions and hypotheses, experimental design and sampling procedures, and common statistical methods in that context. Each statistical method is discussed in a concrete context of a set of research question with directed (one-sided) or undirected (two-sided) hypotheses and an experimental setup in line with these questions and hypotheses. Therefore, the titles of the chapters in this book do not include any names of statistical methods such as ‘analysis of variance’ or ‘analysis of covariance’. In a total of seventeen chapters, this book covers a wide range of topics of research questions that call for experimental designs and statistical methods, fairly basic or more advanced.
Author : Glen Cowan
Publisher : Oxford University Press
Page : 218 pages
File Size : 50,36 MB
Release : 1998
Category : Mathematics
ISBN : 0198501560
This book is a guide to the practical application of statistics in data analysis as typically encountered in the physical sciences. It is primarily addressed at students and professionals who need to draw quantitative conclusions from experimental data. Although most of the examples are takenfrom particle physics, the material is presented in a sufficiently general way as to be useful to people from most branches of the physical sciences. The first part of the book describes the basic tools of data analysis: concepts of probability and random variables, Monte Carlo techniques,statistical tests, and methods of parameter estimation. The last three chapters are somewhat more specialized than those preceding, covering interval estimation, characteristic functions, and the problem of correcting distributions for the effects of measurement errors (unfolding).
Author : John Robert Green
Publisher :
Page : 382 pages
File Size : 24,81 MB
Release : 1978
Category : Mathematical statistics
ISBN : 9780444416896
Author : Ajit C. Tamhane
Publisher : John Wiley & Sons
Page : 724 pages
File Size : 16,69 MB
Release : 2012-09-12
Category : Science
ISBN : 1118491432
A indispensable guide to understanding and designing modern experiments The tools and techniques of Design of Experiments (DOE) allow researchers to successfully collect, analyze, and interpret data across a wide array of disciplines. Statistical Analysis of Designed Experiments provides a modern and balanced treatment of DOE methodology with thorough coverage of the underlying theory and standard designs of experiments, guiding the reader through applications to research in various fields such as engineering, medicine, business, and the social sciences. The book supplies a foundation for the subject, beginning with basic concepts of DOE and a review of elementary normal theory statistical methods. Subsequent chapters present a uniform, model-based approach to DOE. Each design is presented in a comprehensive format and is accompanied by a motivating example, discussion of the applicability of the design, and a model for its analysis using statistical methods such as graphical plots, analysis of variance (ANOVA), confidence intervals, and hypothesis tests. Numerous theoretical and applied exercises are provided in each chapter, and answers to selected exercises are included at the end of the book. An appendix features three case studies that illustrate the challenges often encountered in real-world experiments, such as randomization, unbalanced data, and outliers. Minitab® software is used to perform analyses throughout the book, and an accompanying FTP site houses additional exercises and data sets. With its breadth of real-world examples and accessible treatment of both theory and applications, Statistical Analysis of Designed Experiments is a valuable book for experimental design courses at the upper-undergraduate and graduate levels. It is also an indispensable reference for practicing statisticians, engineers, and scientists who would like to further their knowledge of DOE.