Economics, Business & Management, Statistics
Cover
Title
Pub'd
Price
(net)
Price
(gross)*
Oct-06
€ 17,95
£ 14,00
€ 19,21
sFr 33,00
Sep-06
€ 39,95
£ 30,50
€ 42,75
sFr 73,00
Statistical Reasoning in Medicine
The successful Statistical Reasoning in Medicine: The Intuitive P-value Primer, with its novel
emphasis on patient and community protection, illustrated the correct use of statistics in health
care research for healthcare workers. Through clear explanations and examples, this book
provided the non-mathematician with a foundation for understanding the underlying statistical
reasoning process in clinical research, the core principles of research design, and the correct use
of statistical inference and p-values.The P-Value Primer 2nd Edition levels the learning curve of
statistics for health care researchers by further de-emphasizing mathematical and computational
devices, bringing the principles of statistical reasoning closer to the uninitiated. Adding to the
updated discussions of research design, hypothesis testing, regression analysis, and Bayes
procedures, are new discussions of absolute and relative risk, as well as a lucid description of
Aug-06
the number needed to treat (NNT). The multiple analysis issue is clearly defined, and a new
description of the correct use and interpretation of combined endpoints in health care research is
offered in an easily digestible format. The P-value Primer 2nd Edition demolishes other
obstacles that have impeded a clear understanding of the application of statistics in medicine.
The intertwined roles of epidemiology and biostatistics are depicted. In addition to a description
of the non-technical history of statistics, a new discussion describes the active cultural forces
that have historically argued against the use of probability and statistics, placing the current
applications and controversies involving p-values in context. New illustrations of the difficulties
physicians and health care providers face in research are offered, and the differences between
research skills and statistical skills are distinguished.
€ 44,95
£ 34,50
€ 48,10
sFr 82,00
Luderer, Bernd; Nollau, Volker; Vetters, Klaus
Mathematical Formulas for Economists
The present collection of formulas has been composed for students of economics or
management science at universities, colleges and trade schools. It contains basic knowledge in
mathematics, financial mathematics and statistics in a compact and clearly arranged form. This
volume is meant to be a reference work to be used by students of undergraduate courses
together with a textbook and by researchers in need of exact statements of mathematical results.
People dealing with practical or applied problems will also find this collection to be an efficient
and easy-to-use work of reference.
3rd ed., 2007, X, 188 p. 62 illus., Softcover
ISBN: 978-3-540-46901-8 / ISBN10: 3-540-46901-X
Harris, Tom
Start-up
Start-up is a user guide for aspiring entrepreneurs and provides expert advice and guidance on
every aspect of launching a new business. It will be of particular value if you are an academic
wishing to exploit the commercial value of a new technology or business solution through the
creation of a new company. Step-by-step, this inspiring and highly readable book covers how to
evaluate the strength of your business idea, how to protect your invention, what legal steps and
responsibilities are involved in forming a company, how to position your products in the
market, how to create a business plan and raise finance.
The case studies, practical exercises and tips in this book will help to demystify the process of
starting a new business, give you the confidence to do it and greatly increase your chances of
realising your dream.
2006, VIII, 165 p. 25 illus., Hardcover
ISBN: 978-3-540-32981-7 / ISBN10: 3-540-32981-1
Moyé, Lemuel A.
2nd ed., 2006, XX, 301 p., Softcover
ISBN: 978-0-387-32913-0 / ISBN10: 0-387-32913-7
SPRINGER TITLES IN: Economics, Business & Management, Statistics
PAGE 1 OF 2
Frühwirth-Schnatter, Sylvia
Finite Mixture and Markov Switching Models
The prominence of finite mixture modelling is greater than ever. Many important statistical
topics like clustering data, outlier treatment, or dealing with unobserved heterogeneity involve
finite mixture models in some way or other. The area of potential applications goes beyond
simple data analysis and extends to regression analysis and to non-linear time series analysis
using Markov switching models.
For more than the hundred years since Karl Pearson showed in 1894 how to estimate the five
parameters of a mixture of two normal distributions using the method of moments, statistical
inference for finite mixture models has been a challenge to everybody who deals with them. In
the past ten years, very powerful computational tools emerged for dealing with these models
which combine a Bayesian approach with recent Monte simulation techniques based on Markov
chains. This book reviews these techniques and covers the most recent advances in the field,
among them bridge sampling techniques and reversible jump Markov chain Monte Carlo
methods.
It is the first time that the Bayesian perspective of finite mixture modelling is systematically
presented in book form. It is argued that the Bayesian approach provides much insight in this
Aug-06
context and is easily implemented in practice. Although the main focus is on Bayesian
inference, the author reviews several frequentist techniques, especially selecting the number of
components of a finite mixture model, and discusses some of their shortcomings compared to
the Bayesian approach.
The aim of this book is to impart the finite mixture and Markov switching approach to statistical
modelling to a wide-ranging community. This includes not only statisticians, but also biologists,
economists, engineers, financial agents, market researcher, medical researchers or any other
frequent user of statistical models. This book should help newcomers to the field to understand
how finite mixture and Markov switching models are formulated, what structures they imply on
the data, what they could be used for, and how they are estimated. Researchers familiar with the
subject also will profit from reading this book. The presentation is rather informal without
abandoning mathematical correctness. Previous notions of Bayesian inference and Monte Carlo
simulation are useful but not needed.
€ 69,95 € 74,85
£ 54,00 sFr 123,50
(Series: Springer Series in Statistics)
2006, XIX, 492 p., Hardcover
ISBN: 978-0-387-32909-3 / ISBN10: 0-387-32909-9
*€ and sFr are recommended prices in Germany and Switzerland. All € and £ prices are net prices subject to local VAT, e.g. in Germany 7%.
All prices exclusive of carriage charges. Prices and other details are subject to change without notice. All errors and omissions excepted.
SPRINGER TITLES IN: Economics, Business & Management, Statistics
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