Statistical Methods for Astronomical Data Analysis

Asis Kumar Chattopadhyay

at 250 WPM

6h 4m

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13

days at 30 min/day

364

total minutes

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Statistical Methods for Astronomical Data Analysis

by Asis Kumar Chattopadhyay, Tanuka Chattopadhyay

Oct 02, 2014

Springer

364

9781493915088

1493915088

Description

This book introduces “Astrostatistics” as a subject in its own right with rewarding examples, including work by the authors with galaxy and Gamma Ray Burst data to engage the reader. This includes a comprehensive blending of Astrophysics and Statistics. The first chapter’s coverage of preliminary concepts and terminologies for astronomical phenomenon will appeal to both Statistics and Astrophysics readers as helpful context. Statistics concepts covered in the book provide a methodological framework. A unique feature is the inclusion of different possible sources of astronomical data, as well as software packages for converting the raw data into appropriate forms for data analysis. Readers can then use the appropriate statistical packages for their particular data analysis needs. The ideas of statistical inference discussed in the book help readers determine how to apply statistical tests. The authors cover different applications of statistical techniques already developed or specifically introduced for astronomical problems, including regression techniques, along with their usefulness for data set problems related to size and dimension. Analysis of missing data is an important part of the book because of its significance for work with astronomical data. Both existing and new techniques related to dimension reduction and clustering are illustrated through examples. There is detailed coverage of applications useful for classification, discrimination, data mining and time series analysis. Later chapters explain simulation techniques useful for the development of physical models where it is difficult or impossible to collect data. Finally, coverage of the many R programs for techniques discussed makes this book a fantastic practical reference. Readers may apply what they learn directly to their data sets in addition to the data sets included by the authors.

Frequently Asked Questions

How many pages are in Statistical Methods for Astronomical Data Analysis?

This edition of Statistical Methods for Astronomical Data Analysis has approximately 364 pages. Please note, this is an estimate and the exact page count can vary between hardcover, paperback, and e-book versions.

How long does it take to read Statistical Methods for Astronomical Data Analysis?

For most readers, Statistical Methods for Astronomical Data Analysis typically takes between 7h 35m and 5h 3m to complete. This is based on the book's length of approximately 91,000 words and common reading speeds.

Here's a detailed breakdown: • Continuous reading at 250 WPM: approximately 6h 4m of focused reading • Casual reading (30 minutes/day): you could finish in roughly 13 days • Estimated word count: 91,000 words

Your individual reading time will vary based on your personal reading pace, the amount of daily reading time, and your familiarity with the subject matter.

What is the word count of Statistical Methods for Astronomical Data Analysis?

The estimated word count for Statistical Methods for Astronomical Data Analysis is approximately 91,000 words. This figure is calculated using industry-standard methods that consider genre-specific word density patterns, typical formatting and layout characteristics, and standard words-per-page ratios for published books.

This is an approximation — actual word count may vary based on font size, formatting, edition, and the presence of illustrations or charts.

Who is the author of Statistical Methods for Astronomical Data Analysis?

Statistical Methods for Astronomical Data Analysis was written by Asis Kumar Chattopadhyay, Tanuka Chattopadhyay.

When was Statistical Methods for Astronomical Data Analysis published?

The publication date for this specific edition is Oct 02, 2014. The original work may have been published on a different date.