Mathematics, Computers - Rukh Creators – Digital Marketing Agency UAE & KSA

July 10, 2026
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Introducing Monte Carlo Methods with R (Use R!) by George Casella

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July 10, 2026
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MONTE CARLO STATISTICAL METHODS (SPRINGER TEXTS IN STATISTICS) BY George Casella

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July 10, 2026
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Monte Carlo Statistical – Hardcover, by Robert Christian; Casella – Very Good

You will find that this textbook includes a wide range of perspectives on the topic.

July 10, 2026
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MONTE CARLO STATISTICAL METHODS 2nd EDITION BOOK SPRINGER TEXTS IN STATISTICS

You will find that this textbook has a companion website with extra resources.

July 10, 2026
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Introducing Monte Carlo Methods – Paperback, by Christian P. Robert; – Very Good

This textbook is in great condition, with no writing or highlighting inside.

July 10, 2026
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Applied Statistical Inference with MINITAB®, Second Edition by Sally A. Lesik…

What stands out about this textbook is how it balances depth and readability.

July 9, 2026
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C. H. DAGLI – Intelligent Engineering Systems Neural Networks Vol 5 | NEW

What stands out about this textbook is the step-by-step problem-solving approach.

July 9, 2026
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PowerShell for Beginners: Learn PowerShell 7 Through Hands-On Mini Games, Waters

You will find that the mini size encourages you to read a little each day.

July 9, 2026
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SOLVING COMBINATORIAL OPTIMIZATION PROBLEMS IN PARALLEL By Alfonso NEW

SOLVING COMBINATORIAL OPTIMIZATION PROBLEMS IN PARALLEL METHODS AND TECHNIQUES (LECTURE NOTES IN COMPUTER SCIENCE) By Alfonso Ferreira & Panos Pardalos **BRAND NEW**.

July 9, 2026
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An Introduction to Statistical Learning: With Applications in R by James VG COND

“An Introduction to Statistical Learning: With Applications in R” is a comprehensive textbook by authors Trevor Hastie, Gareth James, Robert Tibshirani, and Daniela Witten. Published by Springer New York in 2017, this hardcover book covers a range of topics in mathematics and statistics, including machine learning and data analysis. With 426 pages and in English, this textbook is a valuable resource for students and professionals in the field of statistical learning. The book also includes practical applications in R, making it a practical and informative tool for those looking to deepen their understanding of statistical methods.

Item Tag: Mathematics, Computers