Listing 1 - 6 of 6 |
Sort by
|
Choose an application
This volume presents the basic mathematics of ranking methods through a didactic approach and the integration of relevant applications. Ranking methods can be applied in several different fields, including decision support, toxicology, environmental problems, proteomics and genomics, analytical chemistry, food chemistry, and QSAR.. Covers a wide range of applications, from the environment and toxicology to DNA sequencing. Incorporates contributions from renowned experts in the field. Meets the increasing demand for literature concerned with ranking methods and their application
Science --- Ranking and selection (Statistics) --- Statistical methods. --- Mathematical statistics --- Order statistics --- Selection and ranking (Statistics)
Choose an application
"Ranked Set Sampling: 65 Years Improving the Accuracy in Data Gathering is an advanced survey technique which seeks to improve the likelihood that collected sample data presents a good representation of the population and minimizes the costs associated with obtaining them. The main focus of many agricultural, ecological and environmental studies is the development of well designed, cost-effective and efficient sampling designs, giving RSS techniques a particular place in resolving the disciplinary problems of economists in application contexts, particularly experimental economics. This book seeks to place RSS at the heart of economic study designs."--Back cover.
Sampling (Statistics) --- Ranking and selection (Statistics) --- Selection and ranking (Statistics) --- Mathematical statistics --- Order statistics --- Random sampling --- Statistics of sampling --- Statistics
Choose an application
Nonparametric statistics provide a scientific methodology for cases where customary statistics are not applicable. Nonparametric statistics are used when the requirements for parametric analysis fail, such as when data are not normally distributed or the sample size is too small. The method provides an alternative for such cases and is often nearly as powerful as parametric statistics. Another advantage of nonparametric statistics is that it offers analytical methods that are not available otherwise. In social sciences, often, it is not possible to obtain measurements, which renders customary analysis impossible. For example, it is not possible to measure utility but is possible to rank preference, which is based on the unmeasurable utility. Nonparametric methods provide theoretically valid options for analysis, making the use of unscientific methods unnecessary. Nonparametric methods are intuitive and simple to comprehend, which helps researchers in the social sciences understand the methods in spite of lacking mathematical rigor needed in analytical methods customarily used in science. The only prerequisite for this book is high school level elementary algebra. This book is a methodology book and bypasses theoretical proofs while providing comprehensive explanations of the logic behind the methods and ample examples, which are all solved using direct computations as well as by using Stata. The book is arranged into two integrated volumes. Although each volume, and for that matter each chapter, can be used separately, it is advisable to read as much of both volumes as possible; because familiarity with what is applicable for different problems will enhance capabilities. It is recommended that everyone read the Introduction and Chapter 1 because determining whether data are random or normally distributed is essential in the selection of parametric versus nonparametric methods.
Nonparametric statistics. --- Nonparametric statistics --- median --- order statistics --- rank --- one sample --- two samples --- several samples --- multiple comparison --- normality --- skewness
Choose an application
Nonparametric statistics provide a scientific methodology for cases where customary statistics are not applicable. Nonparametric statistics are used when the requirements for parametric analysis fail, such as when data are not normally distributed or the sample size is too small. The method provides an alternative for such cases and is often nearly as powerful as parametric statistics. Another advantage of nonparametric statistics is that it offers analytical methods that are not available otherwise. In social sciences, often, it is not possible to obtain measurements, which renders customary analysis impossible. For example, it is not possible to measure utility but is possible to rank preference, which is based on the unmeasurable utility. Nonparametric methods provide theoretically valid options for analysis, making the use of unscientific methods unnecessary. Nonparametric methods are intuitive and simple to comprehend, which helps researchers in the social sciences understand the methods in spite of lacking mathematical rigor needed in analytical methods customarily used in science. The only prerequisite for this book is high school level elementary algebra. This book is a methodology book and bypasses theoretical proofs while providing comprehensive explanations of the logic behind the methods and ample examples, which are all solved using direct computations as well as by using Stata. The book is arranged into two integrated volumes. Although each volume, and for that matter each chapter, can be used separately, it is advisable to read as much of both volumes as possible; because familiarity with what is applicable for different problems will enhance capabilities. It is recommended that everyone read the Introduction and Chapter 1 because determining whether data are random or normally distributed is essential in the selection of parametric versus nonparametric methods.
Nonparametric statistics. --- Nonparametric statistics --- median --- order statistics --- rank --- one sample --- two samples --- several samples --- multiple comparison --- normality --- skewness
Choose an application
This title provides an account of a new theory and method of voting, judging and ranking, 'majority judgement', shown to be superior to all other known methods.
Social choice --- Voting --- Ranking and selection (Statistics) --- Operational research. Game theory --- Social choice. --- Voting. --- Selection and ranking (Statistics) --- Mathematical statistics --- Order statistics --- Polls --- Elections --- Politics, Practical --- Suffrage --- Choice, Social --- Collective choice --- Public choice --- Choice (Psychology) --- Social psychology --- Welfare economics --- SOCIAL SCIENCES/Political Science/General --- E-books --- Balloting
Choose an application
The first edition of Theory of Rank Tests (1967) has been the precursor to a unified and theoretically motivated treatise of the basic theory of tests based on ranks of the sample observations. For more than 25 years, it helped raise a generation of statisticians in cultivating their theoretical research in this fertile area, as well as in using these tools in their application oriented research. The present edition not only aims to revive this classical text by updating the findings but also by incorporating several other important areas which were either not properly developed before
Ranking and selection (Statistics) --- Statistical hypothesis testing. --- Hypothesis testing (Statistics) --- Significance testing (Statistics) --- Statistical significance testing --- Testing statistical hypotheses --- Selection and ranking (Statistics) --- Distribution (Probability theory) --- Hypothesis --- Mathematical statistics --- Order statistics --- 519.244 --- 519.244 Sequential methods. Optimal stopping. Cusum technique (cumulative sum technique) --- Sequential methods. Optimal stopping. Cusum technique (cumulative sum technique) --- Rang et sélection (Statistique) --- Tests d'hypothèses (Statistique) --- ELSEVIER-B EPUB-LIV-FT
Listing 1 - 6 of 6 |
Sort by
|