Skip to content

Booksellers & Trade Customers: Sign up for online bulk buying at trade.atlanticbooks.com for wholesale discounts

Booksellers: Create Account on our B2B Portal for wholesale discounts

The Architecture of Randomness: The Construction of Modern Statistics with Measure Theory

by Busra Hkt
Sold out
Current price ₹1,866.00
Original price ₹2,075.00
Original price ₹2,075.00
Original price ₹2,075.00
(-10%)
₹1,866.00
Current price ₹1,866.00

Imported Edition - Ships in 18-21 Days

Free Shipping in India on orders above Rs. 500

Request Bulk Quantity Quote
+91
Book cover type: Paperback
  • ISBN13: 9798250418102
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Publication Date:
  • Pages: 256
  • Original Price: GBP 16.4
  • Language: English
  • Edition: N/A
  • Item Weight: 345 grams
  • BISAC Subject(s): Probability & Statistics / General

Master the Mathematical Foundations of Modern Statistics

Modern statistics is not built on formulas alone - it is constructed upon the rigorous architecture of measure theory, probability spaces, and functional analysis. This book provides a deep, systematic, and axiomatic exploration of the mathematical foundations that shape contemporary probability theory and statistical modeling.

From sigma-algebras and Lebesgue measure to Radon-Nikodym derivatives, conditional expectation, martingales, and statistical decision theory, the reader is guided through the structural backbone of modern stochastic analysis.

Designed for serious learners, researchers, and professionals, this work bridges pure measure theory with advanced probability and the theoretical framework of statistical inference.


Who Should Read This Book?
  • Graduate students in mathematics, statistics, or applied mathematics

  • PhD candidates working in probability theory or statistical modeling

  • Researchers in stochastic processes and mathematical statistics

  • Data scientists seeking deep theoretical foundations

  • Academics teaching measure-theoretic probability

  • Anyone transitioning from classical probability to rigorous modern probability theory


Questions Answered in This Book
  • How is Lebesgue measure constructed from outer measure?

  • What makes a function measurable?

  • Why is the Radon-Nikodym theorem fundamental to modern probability?

  • How is expectation defined in measure-theoretic terms?

  • What is the rigorous structure behind conditional expectation?

  • How do product measures lead to Fubini and Tonelli theorems?

  • What is the role of independence in structural probability theory?

  • How does measure theory form the backbone of modern statistical models?

  • How are likelihood, sufficiency, and Fisher information defined rigorously?

  • What connects probability measures to statistical decision theory?


Core Topics Covered

Measure theory foundations
Sigma-algebras and measurable functions
Carath�odory construction
Lebesgue integral and Lp spaces
Product measures and infinite dimensional constructions
Kolmogorov axioms and probability spaces
Radon-Nikodym theorem
Conditional expectation and martingales
Independence and zero-one laws
Parametric statistical models
Likelihood theory and Fisher information
Measure-theoretic decision theory

This book is ideal for readers who demand mathematical precision, structural clarity, and conceptual depth.

Trusted for over 49 years

Family Owned Company

Secure Payment

All Major Credit Cards/Debit Cards/UPI & More Accepted

New & Authentic Products

India's Largest Distributor

Need Support?

Whatsapp Us