Signal 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


Signal

简体网页||繁体网页
Stephen Few 作者
Analytics Press
译者
2015-6 出版日期
225 页数
USD 45.00 价格
Hardcover
丛书系列
9781938377051 图书编码

Signal 在线电子书 图书标签: 数据科学   


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发表于2024-11-08


Signal 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Signal 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Signal 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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Signal 在线电子书 著者简介

Stephen Few is on mission to help organizations squeeze real value from the mounds of data that surround and threaten to bury them. Through his consultancy, Perceptual Edge, Stephen teaches simple, clear, and practical data visualization techniques for exploring, analyzing, and presenting quantitative information. He speaks, teaches, and consults internationally, writes the quarterly Visual Business Intelligence Newsletter, and is the author of three other best-selling books on data visualization: Show Me the Numbers: Designing Tables and Graphs to Enlighten, Information Dashboard Design: Displaying Data for At-a-Glance Monitoring, and Now You See It: Simple Visualization Techniques for Quantitative Analysis.


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Signal 在线电子书 图书描述

In this age of so-called Big Data, organizations are scrambling to implement new software and hardware to increase the amount of data they collect and store. However, in doing so they are unwittingly making it harder to find the needles of useful information in the rapidly growing mounds of hay. If you don't know how to differentiate signals from noise, adding more noise only makes things worse. When we rely on data for making decisions, how do we tell what qualifies as a signal and what is merely noise? In and of itself, data is neither. Assuming that data is accurate, it is merely a collection of facts. When a fact is true and useful, only then is it a signal. When it's not, it's noise. It's that simple. In Signal, Stephen Few provides the straightforward, practical instruction in everyday signal detection that has been lacking until now. Using data visualization methods, he teaches how to apply statistics to gain a comprehensive understanding of one's data and adapts the techniques of Statistical Process Control in new ways to detect not just changes in the metrics but also changes in the patterns that characterize data.

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