From Algorithms to Z-Scores: Probabilistic and Statistical Modeling in Computer Science

A textbook for a course in mathematical probability and statistics for computer science students.

**Tag(s):**
Probability
Statistics

**Publication date**: 01 Jun 2015

**ISBN-10**:
n/a

**ISBN-13**:
n/a

**Paperback**:
543 pages

**Views**: 9,741

**Type**: Textbook

**Publisher**:
n/a

**License**:
Creative Commons Attribution-No Derivative Works 3.0 United States License

**Post time**: 19 Jul 2016 02:00:00

From Algorithms to Z-Scores: Probabilistic and Statistical Modeling in Computer Science

A textbook for a course in mathematical probability and statistics for computer science students.

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The licensor cannot revoke these freedoms as long as you follow the license terms.

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From the Preface:

More information is available at the book webpage.

Norman Matloff wrote:Why is this book different from all other books on mathematical probability and statistics? The key aspect is the book's consistently applied approach, especially important for engineering students.

Norman Matloff wrote:As prerequisites, the student must know calculus, basic matrix algebra, and have some skill in programming. As with any text in probability and statistics, it is also necessary that the student has a good sense of math intuition, and does not treat mathematics as simply memorization of formulas.

More information is available at the book webpage.

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About The Author(s)

Dr. Norm Matloff is a professor of computer science at the University of California at Davis, and was formerly a professor of statistics at that university. He is a former database software developer in Silicon Valley, and has been a statistical consultant for firms such as the Kaiser Permanente Health Plan. He was born and raised in the Los Angeles area, and has a PhD in pure mathematics from UCLA, specializing in probability/functional analysis and statistics.

Book Categories

Computer Science
Introduction to Computer Science
Introduction to Computer Programming
Algorithms and Data Structures
Artificial Intelligence
Computer Vision
Machine Learning
Neural Networks
Game Development and Multimedia
Data Communication and Networks
Coding Theory
Computer Security
Information Security
Cryptography
Information Theory
Computer Organization and Architecture
Operating Systems
Image Processing
Parallel Computing
Concurrent Programming
Relational Database
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Data Mining
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Compiler Design and Construction
Functional Programming
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Linear Algebra
Number Theory
Numerical Methods
Precalculus
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Category Theory
Proofs
Discrete Mathematics
Theory of Computation
Graph Theory
Real Analysis
Complex Analysis
Probability
Statistics
Game Theory
Queueing Theory
Operations Research
Computer Aided Mathematics

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Electric Circuits
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Signal Processing
Integration and Automation
Network Science
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