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Titlebook: Better Business Decisions from Data; Statistical Analysis Peter Kenny Book 2014 Peter Kenny 2014

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發(fā)表于 2025-3-21 17:16:59 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Better Business Decisions from Data
期刊簡(jiǎn)稱Statistical Analysis
影響因子2023Peter Kenny
視頻videohttp://file.papertrans.cn/185/184824/184824.mp4
發(fā)行地址Better Business Decisions from Data: Statistical Analysis for Professional Success is a guide to making better business decisions by extracting valuable information from statistical data--and avoiding
圖書封面Titlebook: Better Business Decisions from Data; Statistical Analysis Peter Kenny Book 2014 Peter Kenny 2014
影響因子.Everyone encounters statistics on a daily basis. They are used in proposals, reports, requests, and advertisements, among others, to support assertions, opinions, and theories. Unless you’re a trained statistician, it can be bewildering. What are the numbers really saying or not saying? .Better Business Decisions from Data: Statistical Analysis for Professional Success. provides the answers to these questions and more. It will show you how to use statistical data to improve small, every-day management judgments as well as major business decisions with potentially serious consequences..Author Peter Kenny—with deep experience in industry—believes that "while the methods of statistics can be complicated, the meaning of statistics is not." He first outlines the ways in which we are frequently misled by statistical results, either because of our lack of understanding or because we are being misled intentionally. Then he offers sound approaches for understanding and assessing statistical data to make excellent decisions. Kenny assumes no prior knowledge of statistical techniques; he explains concepts simply and shows how the tools are used in various business situations..With the arriva
Pindex Book 2014
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Sources of Uncertainty correct. However, in statistical investigations there are additional sources of uncertainty, because of the need to extract a neat and useful conclusion from information that may be extensive and variable.
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The Raw Datadata” or “new data” would have been more inviting, but I have to stick to convention. The purpose of this chapter is to explain the different kinds of data and present a number of definitions to be used in the chapters that follow. In addition, I will demonstrate how figures can mislead or confuse e
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Comparisons with Numerical Dataor similarities. This chapter explains what can be learned from single values, pairs of values, pairs of samples, and sets of samples. In each case, the null hypothesis, that no difference is evidenced, is set up; and, by calculating the appropriate test statistic, it is established whether the null
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