Statistical Thinking from Scratch

This book PDF is perfect for those who love Science genre, written by M. D. Edge and published by Oxford University Press which was released on 07 June 2019 with total hardcover pages 320. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Statistical Thinking from Scratch books below.

Statistical Thinking from Scratch
Author : M. D. Edge
File Size : 46,5 Mb
Publisher : Oxford University Press
Language : English
Release Date : 07 June 2019
ISBN : 9780192562708
Pages : 320 pages
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Statistical Thinking from Scratch by M. D. Edge Book PDF Summary

Researchers across the natural and social sciences find themselves navigating tremendous amounts of new data. Making sense of this flood of information requires more than the rote application of formulaic statistical methods. The premise of Statistical Thinking from Scratch is that students who want to become confident data analysts are better served by a deep introduction to a single statistical method than by a cursory overview of many methods. In particular, this book focuses on simple linear regression-a method with close connections to the most important tools in applied statistics-using it as a detailed case study for teaching resampling-based, likelihood-based, and Bayesian approaches to statistical inference. Considering simple linear regression in depth imparts an idea of how statistical procedures are designed, a flavour for the philosophical positions one assumes when applying statistics, and tools to probe the strengths of one's statistical approach. Key to the book's novel approach is its mathematical level, which is gentler than most texts for statisticians but more rigorous than most introductory texts for non-statisticians. Statistical Thinking from Scratch is suitable for senior undergraduate and beginning graduate students, professional researchers, and practitioners seeking to improve their understanding of statistical methods across the natural and social sciences, medicine, psychology, public health, business, and other fields.

Statistical Thinking from Scratch

Researchers across the natural and social sciences find themselves navigating tremendous amounts of new data. Making sense of this flood of information requires more than the rote application of formulaic statistical methods. The premise of Statistical Thinking from Scratch is that students who want to become confident data analysts are

Get Book
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Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not

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Since the first athletic events found a fan base, sports and statistics have always maintained a tight and at times mythical relationship. As a way to relay the telling of a game's drama and attest to the prodigious powers of the heroes involved, those reporting on the games tallied up

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Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that

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In this book the Jsopeh Tal, "brings statistics down to earth for the general reader. Focusing on the psychology behind statistics, he shows how it applies in our everyday lives. He demonstrates how even mundane decisions, such as what to make for dinner or whether to take an umbrella, involve

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The Rise of Statistical Thinking  1820   1900

An essential work on the origins of statistics The Rise of Statistical Thinking, 1820–1900 explores the history of statistics from the field's origins in the nineteenth century through to the factors that produced the burst of modern statistical innovation in the early twentieth century. Theodore Porter shows that statistics was not

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