Overview
Provides essential material needed for a first and second course in probability and statistics
Focuses on critical concepts for each topic, motivated by numerous examples and exercises
Presents material in brief, self-contained chapters that can be studied in succession or independently
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About this book
This textbook, now in its third edition, offers a practical introduction to probability with statistical applications, covering material for both a first and second undergraduate probability course. The author focuses on essential concepts that every student should thoroughly understand. The content is organized into brief, easy-to-follow chapters, motivated by plenty of examples.
The first part of the book focuses on classical discrete probability distributions, then goes on to study continuous distributions, confidence intervals, and statistical tests. The following section introduces more advanced concepts suitable for a second course in probability, such as random vectors and sums of random variables. The last part of the book is dedicated to mathematical statistics concepts such as estimation, sufficiency, Bayes' estimation, and multiple regression. This third edition includes a new chapter on combinatorics and a more distinct separation between discrete and continuous distributions. Some of the longer chapters in the previous editions have been divided into shorter chapters to allow for more flexible teaching.
Probability with Statistical Applications, Third Edition is intended for undergraduate students taking a first course in probability; later chapters are also suited for a second course in probability and mathematical statistics. Calculus is the only prerequisite; prior knowledge of probability is not required.
The first part of the book focuses on classical discrete probability distributions, then goes on to study continuous distributions, confidence intervals, and statistical tests. The following section introduces more advanced concepts suitable for a second course in probability, such as random vectors and sums of random variables. The last part of the book is dedicated to mathematical statistics concepts such as estimation, sufficiency, Bayes' estimation, and multiple regression. This third edition includes a new chapter on combinatorics and a more distinct separation between discrete and continuous distributions. Some of the longer chapters in the previous editions have been divided into shorter chapters to allow for more flexible teaching.
Probability with Statistical Applications, Third Edition is intended for undergraduate students taking a first course in probability; later chapters are also suited for a second course in probability and mathematical statistics. Calculus is the only prerequisite; prior knowledge of probability is not required.
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Keywords
Table of contents (29 chapters)
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Front Matter
Authors and Affiliations
About the author
Rinaldo Schinazi is a professor at the University of Colorado Springs. He teaches a wide range of probability and statistics courses. His research is in probability models for population biology.
Bibliographic Information
Book Title: Probability with Statistical Applications
Authors: Rinaldo B. Schinazi
DOI: https://doi.org/10.1007/978-3-030-93635-8
Publisher: Birkhäuser Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-93634-1Published: 27 February 2022
Softcover ISBN: 978-3-030-93637-2Published: 28 February 2023
eBook ISBN: 978-3-030-93635-8Published: 26 February 2022
Edition Number: 3
Number of Pages: XI, 361
Number of Illustrations: 19 b/w illustrations, 4 illustrations in colour
Topics: Probability Theory and Stochastic Processes, Applications of Mathematics, Statistical Theory and Methods, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences