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Foundations of Statistics for Data Scientists: With R and Python
by Agresti, Alan    Kateri, Maria   
(Hardcover - English - 9780367748456)
Foundations of Statistics for Data Scientists: With R and Python is designed as a textbook for a one- or two-term introduction to mathematical statistics for students training to become data scientists. It is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modeling. The book assumes knowledge of basic calculus, so the presentation can focus on "why it works" as well as "how to do it." Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory a ..
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Fundamentals of Data Science Part I: Inference and Experiment
by Maruskin, Jared M.       
(Paperback - English - 9781941043110)
In Partof this series, we cover basic statistical inference and experimentation, focusing on: ul li basic statistics; li li derivation and review of key distributions and their relations; li li hypothesis testing, including an in depth power analysis for the chi-squared statistic; li li experimentation, including Atests, stratification, one- and two-factor experiments, and an introduction to bandit algorithms; li li maximum likelihood; li li gradient descent; li li introduction to survival analysis and stochastic processes, including empirical estimation of online survival and event processes. li ul The theory is illustrated with simulations i ..
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The Python Book
by Mastrodomenico, Rob       
(Paperback - English - 9781119573319)
The Python Book Discover the power of one of the fastest growing programming languages in the world with this insightful new resource The Python Book delivers an essential introductory guide to learning Python for anyone who works with data but does not have experience in programming. The author, an experienced data scientist and Python programmer, shows readers how to use Python for data analysis, exploration, cleaning, and wrangling. Readers will learn what in the Python language is important for data analysis, and why. The Python Book offers readers a thorough and comprehensive introduction to Python that is both simple enough to be ideal for a novice pro ..
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Mathematical Foundations of Infinite-Dimensional Statistical Models
by Giné, Evarist    Nickl, Richard   
(Paperback - English - 9781108994132)
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Fundamentals of Causal Inference: With R
by Brumback, Babette A.       
(Hardcover - English - 9780367705053)
"Overall, this textbook is a perfect guide for interested researchers and students who wish to understand the rationale and methods of causal inference. Each chapter provides an R implementation of the introduced causal concepts and models and concludes with appropriate exercises." br -An-Shun Tai & Sheng-Hsuan Lin, in Biometrics br br One of the primary motivations for clinical trials and observational studies of humans is to infer cause and effect. Disentangling causation from confounding is of utmost importance. Fundamentals of Causal Inference explains and relates different methods of confounding adjustment in terms of potential outcomes and graphi ..
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Rp. 1.999.000
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Sampling: Design and Analysis
by Lohr, Sharon L.       
(Hardcover - English - 9780367279509)
"The level is appropriate for an upper-level undergraduate or graduate-level statistics major. Sampling: Design and Analysis (SDA) will also benefit a non-statistics major with a desire to understand the concepts of sampling from a finite population. A student with patience to delve into the rigor of survey statistics will gain even more from the content that SDA offers. The updates to SDA have potential to enrich traditional survey sampling classes at both the undergraduate and graduate levels. The new discussions of low response rates, non-probability surveys, and internet as a data collection mode hold particular value, as these statistical issues have become ..
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Social Accounting and Economic Models
by Stone, Richard       
(Paperback - English - 9781015144712)
This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical e ..
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Statistics Behind the Headlines
by Bailer, A. John    Pennington, Rosemary   
(Hardcover - English - 9780367902537)
How do you learn about what's going on in the world? Did a news headline grab your attention? Did a news story report on recent research? What do you need to know to be a critical consumer of the news you read? If you are looking to start developing your data self-defense and critical news consumption skills, this book is for you! It reflects a long-term collaboration between a statistician and a journalist to shed light on the statistics behind the stories and the stories behind the statistics. The only prerequisite for enjoying this book is an interest in developing the skills and insights for better understanding news stories that incorporate quantitative inf ..
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Extreme Value Theory with Applications to Natural Hazards: From Statistical Theory to Industrial Practice
by Bousquet, Nicolas    Bernardara, Pietro   
(Paperback - English - 9783030749446)
1 E. Garnier: Extreme Events and History: for a better consideration of natural hazards.- 2 N. Bousquet and P. Bernardara: Introduction.- PartStandard Extreme Value Theory.- 3 P. Bernardara and N. Bousquet: Probabilistic modeling and statistical quantification of natural hazards.- 4 N. Bousquet: Fundamental concepts of probability and statistics.- 5 M. Andreewsky and N. Bousquet: Collecting and analyzing data.- 6 A. Dutfoy: Univariate extreme value theory: practice and limitations.- Part II Elements of Extensive Statistical Analysis.- 7 J. Weiss and M. Andreewsky: Regional extreme value analysis.- 8 S. Parey, T. Hoang: Extreme values of non-stationary time serie ..
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Cybersecurity Analytics
by Verma, Rakesh M.    Marchette, David J.   
(Paperback - English - 9781032401003)
strong Cybersecurity Analytics strong is for the cybersecurity student and professional who wants to learn data science techniques critical for tackling cybersecurity challenges, and for the data science student and professional who wants to learn about cybersecurity adaptations. Trying to build a malware detector, a phishing email detector, or just interested in finding patterns in your datasets? This book can let you do it on your own. Numerous examples and datasets links are included so that the reader can "learn by doing." Anyone with a basic college-level calculus course and some probability knowledge can easily understand most of the material. The book ..
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Principles of Statistical Analysis: Learning from Randomized Experiments
by Arias-Castro, Ery       
(Paperback - English - 9781108747448)
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Dicing with Death: Living by Data
by Senn, Stephen       
(Paperback - English - 9781108999861)
As a result of the COVID-19 pandemic, medical statistics and public health data have become staples of newsfeeds worldwide, with infection rates, deaths, case fatality and the mysterious R figure featuring regularly. However, we don't all have the statistical background needed to translate this information into knowledge. In this lively account, Stephen Senn explains these statistical phenomena and demonstrates how statistics is essential to making rational decisions about medical care. The second edition has been thoroughly updated to cover developments of the last two decades and includes a new chapter on medical statistical challenges of COVID-19, along with ..
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Rp. 516.000
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Advanced R, Second Edition
by Wickham, Hadley       
(Paperback - English - 9780815384571)
Advanced R helps you understand how R works at a fundamental level. It is designed for R programmers who want to deepen their understanding of the language, and programmers experienced in other languages who want to understand what makes R different and special. This book will teach you the foundations of R; three fundamental programming paradigms (functional, object-oriented, and metaprogramming); and powerful techniques for debugging and optimising br your code. By reading this book, you will learn: ul li The difference between an object and its name, and why the distinction is important li li The important vector data structures, how they fit ..
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Rp. 1.669.000
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Matemáticas del Aprendizaje Automático: Introducción a la analítica de datos e inteligencia artificial
by Han, Richard       
(Paperback - Spanish - 9780578507057)
Desde autos que conducen solos y sistemas de recomendaci n hasta el reconocimiento facial y vocal, el aprendizaje autom tico es el camino del futuro. Le gustar a aprender las matem ticas detr s del aprendizaje autom tico para ingresar a los campos de an lisis de datos e inteligencia artificial? No hay muchos recursos que dan ejemplos simples y detallados y que van paso a paso a trav s de los temas del aprendizaje autom tico. Este libro no solo explica qu tipo de matem tica est involucrada y la notaci n confusa, sino que tambi n presenta directamente los temas fundamentales del aprendizaje autom tico. Este libro te ayudar a comenzar aprendizaje autom tico de ..
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Rp. 420.000
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Big Data: Concepts, Technology, and Architecture
by Abirami R., Nandhini    Kadry, Seifedine    Gandomi, Amir H.
(Hardcover - English - 9781119701828)
Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, "Big Data," the book moves on to discuss every stage of the lifecycle of Big Data. You'll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, mac ..
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Rp. 2.681.000
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Statistical testing with jamovi and JASP open source software Health
by Davis, Cole       
(Paperback - English - 9781916063655)
strong Features strong ul li Worked examples from sociology li br li Clearly written, without mathematical formulae li br li Well-structured, for beginners and intermediate readers li br li Comprehensive chapter on categorical analysis br - not just 'Chi squared' li br li Effect sizes and confidence intervals li br li Clear explanation of factor analysis li br li Covers MANOVA, logistic regression and survival analysis li br li Introduces Bayesian statistics li br li Reproduces a well-received short chapter on making presentations li br li Data sets, exercises and case studies on the websit ..
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Rp. 979.000
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Risk Assessment: Theory, Methods, and Applications
by Rausand, Marvin    Haugen, Stein   
(Hardcover - English - 9781119377238)
Introduces risk assessment with key theories, proven methods, and state-of-the-art applications Risk Assessment: Theory, Methods, and Applications remains one of the few textbooks to address current risk analysis and risk assessment with an emphasis on the possibility of sudden, major accidents across various areas of practice--from machinery and manufacturing processes to nuclear power plants and transportation systems. Updated to align with ISO 31000 and other amended standards, this all-new 2nd Edition discusses the main ideas and techniques for assessing risk today. The book begins with an introduction of risk analysis, assessment, and management, and i ..
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Statistical Rethinking: A Bayesian Course with Examples in R and Stan
by McElreath, Richard       
(Hardcover - English - 9780367139919)
Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today's model-based statistics, the book pushes you to perform step-by-step calculations that are usually automated. This unique computational approach ensures that you understand enough of the details to make reasonable choices and interpretations in your own modeling work. The text presents causal inference and generalized linear multilevel models from a simple Bayesian perspective that builds on information theory and maximum entropy. The core material ranges from the basics of regre ..
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Uncertainty Analysis for Engineers and Scientists: A Practical Guide
by Morrison, Faith A.       
(Paperback - English - 9781108745741)
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A First Course in Statistical Programming with R
by Braun, W. John    Murdoch, Duncan J.   
(Paperback - English - 9781108995146)
This third edition of Braun and Murdoch's bestselling textbook now includes discussion of the use and design principles of the tidyverse packages in R, including expanded coverage of ggplot2, and R Markdown. The expanded simulation chapter introduces the Box-Muller and Metropolis-Hastings algorithms. New examples and exercises have been added throughout. This is the only introduction you'll need to start programming in R, the computing standard for analyzing data. This book comes with real R code that teaches the standards of the language. Unlike other introductory books on the R system, this book emphasizes portable programming skills that apply to most computi ..
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