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Statistical Data Analysis

1998 Mathematics
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Release : 1998
Genre : Mathematics
Kind : eBook
Book Rating : 560/5 ( reviews)

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Book Synopsis Statistical Data Analysis by : Glen Cowan

Download or read book Statistical Data Analysis written by Glen Cowan. This book was released on 1998. Available in PDF, EPUB and Kindle. Book excerpt: This book is a guide to the practical application of statistics in data analysis as typically encountered in the physical sciences. It is primarily addressed at students and professionals who need to draw quantitative conclusions from experimental data. Although most of the examples are takenfrom particle physics, the material is presented in a sufficiently general way as to be useful to people from most branches of the physical sciences. The first part of the book describes the basic tools of data analysis: concepts of probability and random variables, Monte Carlo techniques,statistical tests, and methods of parameter estimation. The last three chapters are somewhat more specialized than those preceding, covering interval estimation, characteristic functions, and the problem of correcting distributions for the effects of measurement errors (unfolding).

Practical Statistics for Data Scientists

2017-05-10 Computers
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Release : 2017-05-10
Genre : Computers
Kind : eBook
Book Rating : 911/5 ( reviews)

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Book Synopsis Practical Statistics for Data Scientists by : Peter Bruce

Download or read book Practical Statistics for Data Scientists written by Peter Bruce. This book was released on 2017-05-10. Available in PDF, EPUB and Kindle. Book excerpt: Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data

Statistical Data Analytics

2015-12-21 Mathematics
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Release : 2015-12-21
Genre : Mathematics
Kind : eBook
Book Rating : 65X/5 ( reviews)

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Book Synopsis Statistical Data Analytics by : Walter W. Piegorsch

Download or read book Statistical Data Analytics written by Walter W. Piegorsch. This book was released on 2015-12-21. Available in PDF, EPUB and Kindle. Book excerpt: Solutions Manual to accompany Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery. Extensive solutions using actual data (with sample R programming code) are provided, illustrating diverse informatic sources in genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising and finance, among many others.

Applied Statistical Modeling and Data Analytics

2017-10-27 Science
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Release : 2017-10-27
Genre : Science
Kind : eBook
Book Rating : 804/5 ( reviews)

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Book Synopsis Applied Statistical Modeling and Data Analytics by : Srikanta Mishra

Download or read book Applied Statistical Modeling and Data Analytics written by Srikanta Mishra. This book was released on 2017-10-27. Available in PDF, EPUB and Kindle. Book excerpt: Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciences provides a practical guide to many of the classical and modern statistical techniques that have become established for oil and gas professionals in recent years. It serves as a "how to" reference volume for the practicing petroleum engineer or geoscientist interested in applying statistical methods in formation evaluation, reservoir characterization, reservoir modeling and management, and uncertainty quantification. Beginning with a foundational discussion of exploratory data analysis, probability distributions and linear regression modeling, the book focuses on fundamentals and practical examples of such key topics as multivariate analysis, uncertainty quantification, data-driven modeling, and experimental design and response surface analysis. Data sets from the petroleum geosciences are extensively used to demonstrate the applicability of these techniques. The book will also be useful for professionals dealing with subsurface flow problems in hydrogeology, geologic carbon sequestration, and nuclear waste disposal. - Authored by internationally renowned experts in developing and applying statistical methods for oil & gas and other subsurface problem domains - Written by practitioners for practitioners - Presents an easy to follow narrative which progresses from simple concepts to more challenging ones - Includes online resources with software applications and practical examples for the most relevant and popular statistical methods, using data sets from the petroleum geosciences - Addresses the theory and practice of statistical modeling and data analytics from the perspective of petroleum geoscience applications

Introduction to Statistics and Data Analysis

2023-01-30 Mathematics
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Release : 2023-01-30
Genre : Mathematics
Kind : eBook
Book Rating : 332/5 ( reviews)

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Book Synopsis Introduction to Statistics and Data Analysis by : Christian Heumann

Download or read book Introduction to Statistics and Data Analysis written by Christian Heumann. This book was released on 2023-01-30. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference. The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.

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