Go to main content

Statistics and analysis of scientific data [electronic resource] / Massimiliano Bonamente.

Bonamente, Massimiliano, author.
2022
QA276
Available Online
Formats
Format
BibTeX
MARCXML
TextMARC
MARC
DublinCore
EndNote
NLM
RefWorks
RIS
Add to Basket
Cite
Citation

Linked e-resources

Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks

Details

Title
Statistics and analysis of scientific data [electronic resource] / Massimiliano Bonamente.
Author
Bonamente, Massimiliano, author.
Edition
Third edition.
ISBN
9789811903656 (electronic bk.)
9811903654 (electronic bk.)
9789811903649
9811903646
DOI
https://doi.org/10.1007/978-981-19-0365-6
Published
Singapore : Springer, 2022.
Language
English
Description
1 online resource (491 pages).
Item Number
10.1007/978-981-19-0365-6 doi
Call Number
QA276
Dewey Decimal Classification
519.5
Summary
This book is the third edition of a successful textbook for upper-undergraduate and early graduate students, which offers a solid foundation in probability theory and statistics and their application to physical sciences, engineering, biomedical sciences and related disciplines. It provides broad coverage ranging from conventional textbook content of probability theory, random variables, and their statistics, regression, and parameter estimation, to modern methods including Monte-Carlo Markov chains, resampling methods and low-count statistics. In addition to minor corrections and adjusting structure of the content, particular features in this new edition include: Python codes and machine-readable data for all examples, classic experiments, and exercises, which are now more accessible to students and instructors New chapters on low-count statistics including the Poisson-based Cash statistic for regression in the low-count regime, and on contingency tables and diagnostic testing. An additional example of classic experiments based on testing data for SARS-COV-2 to demonstrate practical applications of the described statistical methods. This edition inherits the main pedagogical method of earlier versionsa theory-then-application approachwhere emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and practical application of the materials. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data as well as exercises and examples to aid the readers' understanding of the topic.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed July 22, 2022).
Series
Graduate texts in physics.
Available in Other Form
Statistics and Analysis of Scientific Data.
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
Theory of Probability
Random Variables and Their Distributions
Three Fundamental Distributions: Binomial, Gaussian and Poisson
The Distribution of Functions of Random Variables
Error Propagation and Simulation of Random Variables
Maximum Likelihood and Other Methods to Estimate Variables
Mean, Median and Average Values of Variables
Hypothesis Testing and Statistics
Maximumlikelihood Methods for Gaussian Data
Multivariable Regression and Generalized Linear Models
Goodness of Fit and Parameter Uncertainty for Gaussian Data
LowCount Statistics
Maximumlikelihood Methods for lowcount Statistics
The linear Correlation Coefficient
Systematic Errors and Intrinsic Scatter.-Regression with Bivariate Errors
Model Comparison
Monte Carlo Methods
Introduction to Markov Chains
Monte Carlo Markov Chains.

Browse Subjects

Show more subjects...

Statistics

from
to
Export