Introduction to probability

By:

Blitzstein, Joseph K

Contributor(s):

Hwang, Jessica

Material type: Text

TextPublication details: Boca Raton CRC Press 2019Edition: 2nd edDescription: xii, 619pISBN:

9781138369917 (hb.)

Subject(s):

DDC classification:

519.2 BLI

Summary: "Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory.　 The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces."

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Book	Plaksha University Library	Mathematics	519.2 BLI (Browse shelf(Opens below))	Checked out	20/03/2024	002726

Browsing Plaksha University Library shelves, Collection: Mathematics Close shelf browser (Hides shelf browser)

Previous								Next
Previous	519.1 MEY Introductory probability and statistical applications	519.1 VEE Probability, statistics and random processes	519.2 BER Introduction to probability	519.2 BLI Introduction to probability	519.2 HAY Probability and statistics: for engineering and scientists	519.2 HAY Probability and statistics: for engineering and scientists	519.2 HOG Probability and statistical inference	Next

"Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory.　

The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces."

There are no comments on this title.

to post a comment.