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Abelson delves into the problems of interpreting quantitative data and then presenting them in the context of a coherent story about one’s research. Get this from a library! Statistics As Principled Argument. [Robert P Abelson] — In this illuminating volume, Robert P. Abelson delves into the too-often dismissed.

Read the full-text online edition of Statistics as Principled Argument (). Author: Gardarg Faekasa Country: Iraq Language: English (Spanish) Genre: Medical Published (Last): 6 August 2006 Pages: 295 PDF File Size: 13.94 Mb ePub File Size: 14.94 Mb ISBN: 179-4-24960-336-1 Downloads: 34724 Price: Free* [ *Free Regsitration Required] Uploader: Abelson delves into the too-often dismissed problems of interpreting quantitative data and then presenting them in the context of a coherent story about one’s research. MAGIC magnitude, articulation, generalization, interestingness, and credibility is Abelson’s way of systematizing our folk-intuitions about the importance or worthwhileness of a particular claim. The focus of the book is that the purpose of statistics is to organize a useful argument from quantitative evidence, using a form of principled rhetoric. Gabriel rated it it was amazing Jul 07, Such systems, by design, exclude the sorts of intellectual peregrinations that are yielding increasing and unexpected rewards in an era of high-throughput science. It’s a rationalist look sattistics the common uses and misuses of the art of statistics, in the realm of advanced application i. Buku persamaan ic dan transistor amplifier design software

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Book ratings by Goodreads. Selected pages Title Page. Statistics As Principled Argument Elementary Arguments and the Role of Chance. No trivia or quizzes yet.

Description In this illuminating volume, Robert P. He uses this system to paint a thought-provoking picture of how fields are advance knowledge systematically. The focus of the book is that the purpose of statistics is to organize a useful argument from quantitative evidence, using a form of principled rhetoric. If you’re not interested in psychology, many of the examples will be unappealing, even though Abelson does explain the necessary background and choose things that are relatively lively. Taylor arhument it liked it Nov 19, Many examples are included to explain the connection of statistics to substantive claims about real phenomena.

Want to Read Currently Reading Read. Review quote “Everyone doing research or planning to do research should read this book. Upon completion of the book, it is hard not to like, because it is authoritative and comprehensive enough, and at the same time, approachable, entertaining and even light-hearted. Christophe Van rated it really liked it Dec 10, Ableson is entertaining enough, argumemt his guidelines Magnitude, Articulation, Generalisation, Interest, and Credibility of argumentplus his 8 laws are excellent esp.

Refresh and try again. Statistics as principled statkstics Robert P. It is well-framed around the title of the book. He prescribes a system that bins results into ticks, significant results supporting a theoretical argument, ax buts, statistically significant exceptions to these arguments.

It addresses statistics in a clear articulate manner from the point of view of the philosophy of statistics. Molly rated it it was ok Apr 01, Rastreie seus pedidos recentes. Ron champion build your own sports car pdf download. From the beginning is explained that the word “statistics” from data banking about real state, but having data is the beginning and not the goal.

Just a moment while we sign you in to your Goodreads account. Jul 08, Michael rated it it was amazing Recommends it for: Farester rated it liked it Apr 21, Similarly, the methodological techniques he talks about are often more applicable to, or widely used in, psychology than other fields. Jan 18, Wilte rated it it was amazing Shelves: Thanks for telling us about the problem. This is not to say the author doesn’t deal with these subjects – Abelson’s review of multiple comparisons, for example, is thorough and helpful. There are several cases where findings, which at first seemed marginal and which would certainly fail MAGIC standards if the authors were choosing their projects by this system came to re-define fields in unexpected ways.