BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences

Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences

Introduction to Probability and Statistics: Principles and Applications for
Stock photo: cover may vary

Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences Hardback - 2002

by Milton, J. Susan; Arnold, Jesse C

Add to wish list
  • Used
  • very good
Used - Very good

Description

McGraw Hill. 4. Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
Ask the seller a question Add to wish list
A$124.79
Free Delivery within USA
Standard delivery: 7 to 14 days
More delivery options
Ships from BooksRun (Pennsylvania, United States)

Details

About BooksRun Pennsylvania, United States

Specialising in: Textbooks
Biblio member since 2016

BooksRun - best place to buy, sell or rent cheap textbooks

Terms of Sale:

30 days return guarantee. 10% restocking fee applies to discretionary returns

Browse books from BooksRun

Reader reviews for Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences

From the publisher

This well-respected text is designed for the first course in probability and statistics taken by students majoring in Engineering and the Computing Sciences. The prerequisite is one year of calculus. The text offers a balanced presentation of applications and theory. The authors take care to develop the theoretical foundations for the statistical methods presented at a level that is accessible to students with only a calculus background. They explore the practical implications of the formal results to problem-solving so students gain an understanding of the logic behind the techniques as well as practice in using them. The examples, exercises, and applications were chosen specifically for students in engineering and computer science and include opportunities for real data analysis.
tracking-