Probability, Random Variables, and Data Analytics with Engineering Applications / by P. Mohana Shankar.
2021
TK1-9971
Linked e-resources
Linked Resource
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Details
Title
Probability, Random Variables, and Data Analytics with Engineering Applications / by P. Mohana Shankar.
Author
Edition
1st ed. 2021.
ISBN
9783030562595
303056259X
9783030562588
303056259X
9783030562588
Published
Cham : Springer International Publishing : Imprint : Springer, 2021.
Language
English
Description
1 online resource (XII, 473 pages 206 illustrations, 202 illustrations in color)
Item Number
10.1007/978-3-030-56259-5 doi
Call Number
TK1-9971
Dewey Decimal Classification
621.382
Summary
This book bridges the gap between theory and applications that currently exist in undergraduate engineering probability textbooks. It offers examples and exercises using data (sets) in addition to traditional analytical and conceptual ones. Conceptual topics such as one and two random variables, transformations, etc. are presented with a focus on applications. Data analytics related portions of the book offer detailed coverage of receiver operating characteristics curves, parametric and nonparametric hypothesis testing, bootstrapping, performance analysis of machine vision and clinical diagnostic systems, and so on. With Excel spreadsheets of data provided, the book offers a balanced mix of traditional topics and data analytics expanding the scope, diversity, and applications of engineering probability. This makes the contents of the book relevant to current and future applications students are likely to encounter in their endeavors after completion of their studies. A full suite of classroom material is included. A solutions manual is available for instructors. Bridges the gap between conceptual topics and data analytics through appropriate examples and exercises; Features 100's of exercises comprising of traditional analytical ones and others based on data sets relevant to machine vision, machine learning and medical diagnostics; Intersperses analytical approaches with computational ones, providing two-level verifications of a majority of examples and exercises.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file
PDF
Available in Other Form
Print version: 9783030562588
Print version: 9783030562601
Print version: 9783030562618
Print version: 9783030562601
Print version: 9783030562618
Linked Resources
Record Appears in
Table of Contents
Chapter 1. Introduction
Chapter 2. Sets, Venn diagrams, Probability and Bayes' Rule
Chapter 3. Concept of a random variable
Chapter 4. Multiple random variables and their Characteristics
Chapter 5. Applications to Data Analytics and Modeling.
Chapter 2. Sets, Venn diagrams, Probability and Bayes' Rule
Chapter 3. Concept of a random variable
Chapter 4. Multiple random variables and their Characteristics
Chapter 5. Applications to Data Analytics and Modeling.