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Decision support using nonparametric statistics

This concise volume covers nonparametric statistics topics that most are most likely to be seen and used from a practical decision support perspective. While many degree programs require a course in parametric statistics, these methods are often inadequate for real-world decision making in business...

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Detalles Bibliográficos
Autor principal: Beatty, Warren
Lenguaje:eng
Publicado: Springer 2018
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-68264-8
http://cds.cern.ch/record/2303145
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author Beatty, Warren
author_facet Beatty, Warren
author_sort Beatty, Warren
collection CERN
description This concise volume covers nonparametric statistics topics that most are most likely to be seen and used from a practical decision support perspective. While many degree programs require a course in parametric statistics, these methods are often inadequate for real-world decision making in business environments. Much of the data collected today by business executives (for example, customer satisfaction opinions) requires nonparametric statistics for valid analysis, and this book provides the reader with a set of tools that can be used to validly analyze all data, regardless of type. Through numerous examples and exercises, this book explains why nonparametric statistics will lead to better decisions and how they are used to reach a decision, with a wide array of business applications. Online resources include exercise data, spreadsheets, and solutions.
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spelling cern-23031452021-04-21T18:55:25Zdoi:10.1007/978-3-319-68264-8http://cds.cern.ch/record/2303145engBeatty, WarrenDecision support using nonparametric statisticsMathematical Physics and MathematicsThis concise volume covers nonparametric statistics topics that most are most likely to be seen and used from a practical decision support perspective. While many degree programs require a course in parametric statistics, these methods are often inadequate for real-world decision making in business environments. Much of the data collected today by business executives (for example, customer satisfaction opinions) requires nonparametric statistics for valid analysis, and this book provides the reader with a set of tools that can be used to validly analyze all data, regardless of type. Through numerous examples and exercises, this book explains why nonparametric statistics will lead to better decisions and how they are used to reach a decision, with a wide array of business applications. Online resources include exercise data, spreadsheets, and solutions.Springeroai:cds.cern.ch:23031452018
spellingShingle Mathematical Physics and Mathematics
Beatty, Warren
Decision support using nonparametric statistics
title Decision support using nonparametric statistics
title_full Decision support using nonparametric statistics
title_fullStr Decision support using nonparametric statistics
title_full_unstemmed Decision support using nonparametric statistics
title_short Decision support using nonparametric statistics
title_sort decision support using nonparametric statistics
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-319-68264-8
http://cds.cern.ch/record/2303145
work_keys_str_mv AT beattywarren decisionsupportusingnonparametricstatistics