
Data Driven Statistical Methods
Peter Sprent(Author)
Chapman & Hall/CRC (Publisher)
1st Edition
Published on 1. December 1997
Book
Hardback
416 pages
978-0-412-79540-4 (ISBN)
Description
Data Driven Statistical Methods is designed for use either as a text book at the undergraduate level, as a source book providing material and suggestions for teachers wishing to incorporate some of its features into more general courses, and also as a self-instruction manual for applied statisticians seeking a simple introduction to many important practical concepts that use the 'data driven' rather than the 'model driven' approach.
Reviews / Votes
"This scholarly book brings together a vast literature on methods for analyzing and modeling rank data...it is a mathematical statistics book in the best sense of the word..."- Short Books Reviews of the ISI
More details
Series
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 27 mm
Weight
790 gr
ISBN-13
978-0-412-79540-4 (9780412795404)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Peter Sprent
Data Driven Statistical Methods
E-Book
12/2019
1st Edition
Routledge
€225.99
Available for download

Peter Sprent
Data Driven Statistical Methods
E-Book
12/2019
1st Edition
Routledge
€225.99
Available for download
Person
Peter Sprent is Emeritus Professor of Statistics at the University of Dundee in Scotland.
Content
Data-Driven Inference. The Bootstrap. Outliers, Contamination, and Robustness. Location Tests for Two Independent Samples. More One- and Two-Sample Tests. Three or More Independent Samples. Designed Experiments. Correlation and Concordance. Bivariate Regression. Other Regression Models and Diagnostics. Categorical Data Analysis. Further Categorical Data Analysis. Data-Driven or Model-Driven? References. Index.