The statistical eyeglasses : the math behind scientific knowledge / Edoardo Milotti.

Format:

Book

Author/Creator:

Milotti, Edoardo, author.

Contributor:

Morgan & Claypool Publishers, publisher.

Institute of Physics (Great Britain), publisher.

Series:

IOP (Series). Release 5.

IOP concise physics

[IOP release 5]

IOP concise physics, 2053-2571

Language:

English

Subjects (All):

Mathematical physics.

Physics--Methodology.

Physics.

Science--Methodology.

Science.

Physical Description:

1 online resource (various pagings) : illustrations (some color).

Distribution:

Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2018]

Other Title:

Math behind scientific knowledge.

Place of Publication:

San Rafael [California] (40 Oak Drive, San Rafael, CA, 94903, USA) : Morgan & Claypool Publishers, [2018]

System Details:

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.

text file

Biography/History:

Edoardo Milotti is Professor of Physics at the University of Trieste, Italy. After working mostly in experimental particle physics, he has also authored papers on noise processes in physics, and on the physics of cancer. His longtime research interests are in the direction of the analysis of experimental data and in the modeling of complex phenomena. He has published over 200 scientific papers in peer-reviewed scientific journals. He lives in Trieste, Italy, with his wife Alessandra.

Summary:

Science often deals with hard-to-see phenomena, and they only stand out and become real when viewed through the lens of complex statistical tools. This book is not a textbook about statistics applied to science--there are already many excellent books to choose from--rather, it gives an overview of the basic principles that physical scientists use to analyze their data and bring out the order of Nature from the fog of background noise.

Contents:

1. Models of nature

2. Randomness

2.1. What is random?

2.2. How does randomness show up in nature?

2.3. Random and deterministic signals

2.4. From noisy data to the likelihood function

3. Bayesian and frequentist approaches to scientific inference

3.1. Bayes' theorem

3.2. The same game, and a mysterious result

3.3. Statistical descriptors

4. The principles of inferential statistics

4.1. Bayes and the likelihood function

4.2. The 'least informative prior'

4.3. The principles of inferential statistics

5. Parametric inference

5.1. Bayesian parametric inference

5.2. Frequentist parametric inference

6. Prior distributions and equiprobable events in the physical sciences

6.1. Elementary Monte Carlo method

6.2. Transformations of random variables by Monte Carlo

6.3. Bertrand's paradox

7. Conclusions : the statistical nature of scientific knowledge.

Notes:

"Version: 20181101"--Title page verso.

"A Morgan & Claypool publication as part of IOP Concise Physics"--Title page verso.

Includes bibliographical references.

Title from PDF title page (viewed on December 14, 2018).

Other Format:

Print version:

ISBN:

9781643271507

9781643271484

OCLC:

1080122266

Access Restriction:

Restricted for use by site license.