Introduction to statistical modelling and inference (Record no. 6147)

MARC details
000 -LEADER
fixed length control field 03037nam a22002057a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240217140542.0
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781032105710
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.54
Item number AIT
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Aitkin, Murray
245 ## - TITLE STATEMENT
Title Introduction to statistical modelling and inference
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc. CRC Press
Place of publication, distribution, etc. Boca Raton
Date of publication, distribution, etc. 2023
300 ## - PHYSICAL DESCRIPTION
Extent xvi, 374 p.
365 ## - TRADE PRICE
Price type code GBP
Price amount 82.99
520 ## - SUMMARY, ETC.
Summary, etc. The complexity of large-scale data sets (“Big Data”) has stimulated the development of advanced<br/>computational methods for analysing them. There are two different kinds of methods to aid this. The<br/>model-based method uses probability models and likelihood and Bayesian theory, while the model-free<br/>method does not require a probability model, likelihood or Bayesian theory. These two approaches<br/>are based on different philosophical principles of probability theory, espoused by the famous<br/>statisticians Ronald Fisher and Jerzy Neyman.<br/>Introduction to Statistical Modelling and Inference covers simple experimental and survey designs,<br/>and probability models up to and including generalised linear (regression) models and some<br/>extensions of these, including finite mixtures. A wide range of examples from different application<br/>fields are also discussed and analysed. No special software is used, beyond that needed for maximum<br/>likelihood analysis of generalised linear models. Students are expected to have a basic<br/>mathematical background in algebra, coordinate geometry and calculus.<br/>Features<br/>• Probability models are developed from the shape of the sample empirical cumulative distribution<br/>function (cdf) or a transformation of it.<br/>• Bounds for the value of the population cumulative distribution function are obtained from the<br/>Beta distribution at each point of the empirical cdf.<br/>• Bayes’s theorem is developed from the properties of the screening test for a rare condition.<br/>• The multinomial distribution provides an always-true model for any randomly sampled data.<br/>• The model-free bootstrap method for finding the precision of a sample estimate has a model-based<br/>parallel – the Bayesian bootstrap – based on the always-true multinomial distribution.<br/>• The Bayesian posterior distributions of model parameters can be obtained from the maximum<br/>likelihood analysis of the model.<br/><br/>This book is aimed at students in a wide range of disciplines including Data Science. The book is<br/>based on the model-based theory, used widely by scientists in many fields, and compares it, in less<br/>detail, with the model-free theory, popular in computer science, machine learning and official<br/>survey analysis. The development of the model-based theory is accelerated by recent developments<br/>in Bayesian analysis.<br/><br/>(https://www.routledge.com/Introduction-to-Statistical-Modelling-and-Inference/Aitkin/p/book/9781032105710)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistical computing
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Multivariate statistics
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistics and Probability
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Book
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Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Bill No Bill Date Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Full call number Accession Number Date last seen Copy number Cost, replacement price Price effective from Koha item type
    Dewey Decimal Classification     Operations Management & Quantitative Techniques SBHPL/INV/1162/2023-2024 27-01-2024 Indian Institute of Management LRC Indian Institute of Management LRC General Stacks 02/17/2024 Sarat Book House Pvt. Ltd. 5820.50   519.54 AIT 005912 02/17/2024 1 8954.62 02/17/2024 Book

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