Elements of Business Statistics

Elements of Business Statistics
Author :
Publisher :
Total Pages : 586
Release :
ISBN-10 : WISC:89096974746
ISBN-13 :
Rating : 4/5 (46 Downloads)

Book Synopsis Elements of Business Statistics by : Robert Riegel

Download or read book Elements of Business Statistics written by Robert Riegel and published by . This book was released on 1927 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Elements of Business Statistics

Elements of Business Statistics
Author :
Publisher :
Total Pages : 558
Release :
ISBN-10 : 0721643515
ISBN-13 : 9780721643519
Rating : 4/5 (15 Downloads)

Book Synopsis Elements of Business Statistics by : R. C. Gulezian

Download or read book Elements of Business Statistics written by R. C. Gulezian and published by . This book was released on 1979 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Elements of Business Statistics

Elements of Business Statistics
Author :
Publisher :
Total Pages : 586
Release :
ISBN-10 : UCAL:$B323262
ISBN-13 :
Rating : 4/5 (62 Downloads)

Book Synopsis Elements of Business Statistics by : Robert Riegel

Download or read book Elements of Business Statistics written by Robert Riegel and published by . This book was released on 1924 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Elements of Statistical Disclosure Control

Elements of Statistical Disclosure Control
Author :
Publisher : Springer Science & Business Media
Total Pages : 273
Release :
ISBN-10 : 9781461301219
ISBN-13 : 1461301211
Rating : 4/5 (19 Downloads)

Book Synopsis Elements of Statistical Disclosure Control by : Leon Willenborg

Download or read book Elements of Statistical Disclosure Control written by Leon Willenborg and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical disclosure control is the discipline that deals with producing statistical data that are safe enough to be released to external researchers. This book concentrates on the methodology of the area. It deals with both microdata (individual data) and tabular (aggregated) data. The book attempts to develop the theory from what can be called the paradigm of statistical confidentiality: to modify unsafe data in such a way that safe (enough) data emerge, with minimum information loss. This book discusses what safe data, are, how information loss can be measured, and how to modify the data in a (near) optimal way. Once it has been decided how to measure safety and information loss, the production of safe data from unsafe data is often a matter of solving an optimization problem. Several such problems are discussed in the book, and most of them turn out to be hard problems that can be solved only approximately. The authors present new results that have not been published before. The book is not a description of an area that is closed, but, on the contrary, one that still has many spots awaiting to be more fully explored. Some of these are indicated in the book. The book will be useful for official, social and medical statisticians and others who are involved in releasing personal or business data for statistical use. Operations researchers may be interested in the optimization problems involved, particularly for the challenges they present. Leon Willenborg has worked at the Department of Statistical Methods at Statistics Netherlands since 1983, first as a researcher and since 1989 as a senior researcher. Since 1989 his main field of research and consultancy has been statistical disclosure control. From 1996-1998 he was the project coordinator of the EU co-funded SDC project.

The Elements of Statistical Learning

The Elements of Statistical Learning
Author :
Publisher : Springer Science & Business Media
Total Pages : 545
Release :
ISBN-10 : 9780387216065
ISBN-13 : 0387216065
Rating : 4/5 (65 Downloads)

Book Synopsis The Elements of Statistical Learning by : Trevor Hastie

Download or read book The Elements of Statistical Learning written by Trevor Hastie and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.

Introduction to Statistics

Introduction to Statistics
Author :
Publisher : Springer
Total Pages : 532
Release :
ISBN-10 : 9783319177045
ISBN-13 : 3319177044
Rating : 4/5 (45 Downloads)

Book Synopsis Introduction to Statistics by : Wolfgang Karl Härdle

Download or read book Introduction to Statistics written by Wolfgang Karl Härdle and published by Springer. This book was released on 2015-12-25 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers all the topics found in introductory descriptive statistics courses, including simple linear regression and time series analysis, the fundamentals of inferential statistics (probability theory, random sampling and estimation theory), and inferential statistics itself (confidence intervals, testing). Each chapter starts with the necessary theoretical background, which is followed by a variety of examples. The core examples are based on the content of the respective chapter, while the advanced examples, designed to deepen students’ knowledge, also draw on information and material from previous chapters. The enhanced online version helps students grasp the complexity and the practical relevance of statistical analysis through interactive examples and is suitable for undergraduate and graduate students taking their first statistics courses, as well as for undergraduate students in non-mathematical fields, e.g. economics, the social sciences etc.

Elements of Probability and Statistics

Elements of Probability and Statistics
Author :
Publisher : Springer
Total Pages : 246
Release :
ISBN-10 : 9783319072548
ISBN-13 : 3319072544
Rating : 4/5 (48 Downloads)

Book Synopsis Elements of Probability and Statistics by : Francesca Biagini

Download or read book Elements of Probability and Statistics written by Francesca Biagini and published by Springer. This book was released on 2016-01-22 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to elementary probability and to Bayesian statistics using de Finetti's subjectivist approach. One of the features of this approach is that it does not require the introduction of sample space – a non-intrinsic concept that makes the treatment of elementary probability unnecessarily complicate – but introduces as fundamental the concept of random numbers directly related to their interpretation in applications. Events become a particular case of random numbers and probability a particular case of expectation when it is applied to events. The subjective evaluation of expectation and of conditional expectation is based on an economic choice of an acceptable bet or penalty. The properties of expectation and conditional expectation are derived by applying a coherence criterion that the evaluation has to follow. The book is suitable for all introductory courses in probability and statistics for students in Mathematics, Informatics, Engineering, and Physics.