Keeping Statistics Honest: How Not to Lie with Statistics https: ... Overview: Statistics Are Not Lies The use of statistics has really gotten a bad name. A Synopsis of How to Lie with Statistics by Darrell Huff When most people hear or read a statistic, they quickly have to decide if the numbers listed are valid or invalid. … Statisticians are still fighting the stereotype that we are geeks with no understanding of business. By contrast, in marketing research, multivariate analysis is normally charged with uncovering “the why” and opaque predictive computer algorithms are less useful. I could give pages of examples, as could anyone working in a specialized field or consulting capacity. "The fact is that, despite its mathematical base, statistics is as much an art as it is a science." Not a statistician, Huff was a journalist who wrote many "how to" articles as a freelancer. The best-selling statistics book in the second half of the 20th century was "How to Lie with Statistics" by Darrel Huff. Duff does a good job of not only explaining what tricks people use on statistics to twist the facts, but he gives poignant examples that were just as relevant when he wrote this book as they are today. Don't be terrorized by numbers, Huff implores. Sadly, there are others who, for whatever reasons, are unconcerned with the truth. “Statistics” can refer to figures or mathematical models, and either can be used to deceive us, are often misinterpreted or can be flat out wrong. Be sure you know what you're talking about! How to Lie with Statistics. Harvard University. How to calculate basic statistics with a spreadsheet (Mean, Median, Mode, Standard Deviation, Correlation Coefficient)
2. How to Lie with Statistics” by Darrell Huff was a great book to read for a student like myself that is entering a course in statistics. This is not easy, however, and cannot be done “by the numbers.” Occasional claims to the contrary, AI cannot yet do this and will never be able to until Artificial General Intelligence is a reality. Rather, I hope you will learn how it is possible to be misled and how to spot "statistical abuse." !�S�a`W��*��G"�x��o���n~�z��{[}̏�즂���B'�
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�k�"�)�sw$�2�cQy�f��eW}#�9��:����iU�OP�y�e "V%. Like attorneys, statisticians are sometimes asked to lie. If "everyone does it" reflects a rare consensus among authentic statistical experts, that is a different matter, but not what I mean here. One way to make profits for the company is to employ statistics in a less-than-thorough manner. Abstract. Main 2020 Developments and Key 2021 Trends in AI, Data Science... AI registers: finally, a tool to increase transparency in AI/ML. Data Science, and Machine Learning. The background photo is of Richard von Mises, one of the most influential statisticians of the 20th century and author of Probability, Statistics and Truth. This is the best-selling statistics book of all time. In contrast, this interview felt more like a lesson on "How NOT to Lie with Statistics." WORKSHOP How Not to Lie with Statistics: Avoiding Common Mistakes in Quantitative Political Science * Gary King, New York University This article identifies a set of serious theoretical mistakes appearing with troublingly high frequency throughout the quantitative political science literature. Whatever the motive, when the buck is passed to you, my advice to statisticians is pass it right back. I just finished reading How Not to Lie with Statistics: Avoiding Common Mistakes in Quantitative Political Science By Gary King, and found a number of really great pieces of advice in it. For example, it does NOT always imply that half the sample is above this value and half below. )�~��K�&�
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�I6Ov'��(tY'��ȏ�a�"�!DC�uG�B�WU:��7��D�$� An experienced and competent statistician knows how to rule out irrelevant models and pick the one that is both robust in a technical sense and most useful to the decision makers. Statisticians can be fooled, too. How to Lie with Statistics (Penguin Business) Paperback – 12 Dec. 1991 by Darrell Huff (Author) › Visit Amazon's Darrell Huff Page. Instead, let me propose a few simple guidelines on how not to lie with statistics by conveying inaccurate information inadvertently. What I found most interesting is how he dissected the "logic" that uses these techniques to explain how CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): We highlight, and suggest ways to avoid, a large number of common misunderstandings in the literature about best practices in qualitative research. How not to lie with statistics: the correct way to summarize benchmark results. You can still get it today! Rating: 9/10. Occam's Razor is an extremely useful guideline, so I am not making a criticism here. “…all models are wrong, but some are useful.”. 22 Pages Posted: 17 Jan 2008. With §ome kinds of mail questionnaire, a .five or ten per cent response is quite high. Authors: Herzog, Michael, Francis, Gregory, Clarke, Aaron Free Preview. ... How to Lie With Statistics. Sometimes I warn new clients and business partners upfront that I ask lots of questions, apologizing in advance so to speak. I could give pages of examples, as could anyone working in a specialized field or consulting capacity. American Journal of Political Science 30(3): 666-687. There is a ton of this code freely downloadable on the internet. Besides outright lies, distortions and deceptions, there are also what have recently come to be called cognitive biases that have long been of concern to statisticians and the scientific community. Computers in other domains. If you are not preparing the final deliverable - statisticians normally do not - make sure your own work is being correctly summarized and interpreted. Be very careful about making assumptions. (Unfortunately, there is some truth to this stereotype.) By eliminating data that does not suit the researcher’s needs, he can make the data say what he wants it to say. These folks may not actually know what they are doing, though, and this all-too-common practice reflects an amateur programmer’s mentality, not that of a statistician or true data scientist. Cross-computing tools and techniques. Working internationally, as I do, I find even a quick summary in English over Skype or by email helps when the deliverable is in a language I do not speak. How to Lie with Statistics, written by Darrel Huff, was first published in 1954. Trying to learn about a statistical method through online searches and blogs can be very risky, even for those trained in statistics. HOW TO LIE WITH STATISTICS And) ofthose whose addresses are known, many win not reply to a questionnaire, particularly a rather personal one. However, How to lie with statistics was as funny as it was informative. The Lowdown: This How to Lie with Statistics Summary is based on the popular book from Darrell Huff, which demonstrates how all numbers can be manipulated, even when they are presented as objective. Returning to cognitive biases, as noted, statisticians and scientists generally have long known how easy it is for their worldview and egos to interfere with their intellects and learning. 1. Keep your analysis and deliverable as simple as possible...but not too simple. We will discuss:
1. �M�! R V C 612 views. Find books like How to Lie with Statistics from the world’s largest community of readers. I could give pages of examples, as could anyone working in a specialized field or consulting capacity. In statistics, it is very difficult to use all the statistics properly and know their strengths and weaknesses. This one should have done … c�?�I�z�0�ފn�k9��x�C�3�AzQuI^��,J]R^]b[��]�W�J�E���!�_Y�k var disqus_shortname = 'kdnuggets'; Mass-produced predictions are not all equally good, however, and not guaranteed to be profitable. Measurement. Here are some takeaways for anyone seeking to … The best-selling statistics book in the second half of the 20th century was "How to Lie with Statistics" by Darrel Huff. (function() { var dsq = document.createElement('script'); dsq.type = 'text/javascript'; dsq.async = true; dsq.src = 'https://kdnuggets.disqus.com/embed.js'; If complex visualizations or videos will be shown to the end users, leave that up to the pros. These mistakes are all based on faulty statistical theory or on erroneous statistical analysis. See all articles by Gary King Gary King. 30, No. How to Lie with Statistics Chapter 3 Notes CHAPTER 3: The little FIgures That Are Not There-”well-biased samples can be employed to produce almost any result anyone may wish. The little book, "How to Lie With Statistics" was written about 1954. It's better to ask too many questions than too few. 3, pp. It’s a must-read for anyone to more intelligently interpret news, media, and even medical research. How (not) to lie with statistics. Dark Data: Why What You Don’t Know Matters. How can you lie with statistics? As a hypothetical example, suppose a teacher wants to apply for a grant to implement a project he has been doing on a pilot basis. Simple misunderstandings can be just as consequential as outright lies and are much more common. Metrics. “How to Lie with Statistics” Precise falsehoods exist for many reasons. “How to Lie with Statistics” Precise falsehoods exist for many reasons. Read More on Amazon Get My Searchable Collection of 250+ Book Notes. That said, serious misinterpretations may occur because of misunderstandings on the part of the person preparing the report or presentation, or because the statistician wasn't communicating clearly. General and reference. It specifically omits problems with the newest and fanciest statistical techniques for two reasons. Any statistic is based on some sample (because the whole population can't be tested) and every sample has some sort of bias, even if the person wanting the statistic tries hard to not create any. The best analysts seem to have a gift for seeing what, in retrospect, seems obvious. It is NOT always the most common value in the sample. It’s also important remember that even automated models are not all the same. With §ome kinds of mail questionnaire, a .five or ten per cent response is quite high. Mark Twain had some thoughts regarding this and I will only suggest it is a bad habit for a statistician to get into. Cross-computing tools and techniques. 3, … Otherwise you’ll probably only confuse or offend your clients and business associates who are not statisticians. This sort of mass-modeling characterizes quite a lot of data science. Whether you encounter statistics at work, at school, or in advertising, you'll remember its simple lessons. Kevin Gray Follow Statistics, Data … Data and elaborate statistical models will not always win debates and it is not unusual for them simply to be dismissed. WORKSHOP How Not to Lie with Statistics: Avoiding Common Mistakes in Quantitative Political Science * Gary King, New York University This article identifies a set of serious theoretical mistakes appearing with troublingly high frequency throughout the quantitative political science literature. "What is truth?" The Lowdown: This How to Lie with Statistics Summary is based on the popular book from Darrell Huff, which demonstrates how all numbers can be manipulated, even when they are presented as objective. Statistics is difficult to explain in everyday language and this is often the cause, but miscommunications and misunderstanding also happen when non-statisticians use jargon to impress without understanding what it means. We can unintentionally deceive others or sucker ourselves, and many of the most important untruths are not deliberate deceptions. The phrase derives from the full sentence, "There are three kinds of lies: lies, damned lies, and statistics. Information systems. Implementing the AdaBoost Algorithm From Scratch, Data Compression via Dimensionality Reduction: 3 Main Methods, A Journey from Software to Machine Learning Engineer. Read How to Lie with Statistics. 1986-03-01 00:00:00 COMPUTING PRACTICES Edgar H. Sibley Panel Editor Using the arithmetic mean to summarize normalized benchmark results leads to mistaken conclusions that can be avoided by using … Read This Interview First, A Rising Library Beating Pandas in Performance, 10 Python Skills They Don’t Teach in Bootcamp. American Journal of Political Science 30(3): 666-687. Whether you encounter statistics at work, at school, or in advertising, you'll remember its simple lessons. Misusing statistics is one of the most powerful ways to lie. If you want to outsmart a crook, learn his tricks—Darrell Huff explains exactly how in the classic How to Lie with Statistics. General and reference. Never show off. These mistakes are all based on faulty statistical theory or on erroneous statistical analysis. Darrell Huff states that statistics can be used to trick people and can be easily interpreted wrongly. You can still get it today! Regardless of what we do for a living, however, all of us are consumers of statistics at work and in our daily lives. Posted Nov 28, 2011 It uses a breezy, non-mathematical approach to making sense of statistics, and to recognizing nonsense when you see it. "It doesn't have to be perfect!" How not to lie with statistics: the correct way to summarize benchmark results How not to lie with statistics: the correct way to summarize benchmark results Fleming, Philip J.; Wallace, John J. Sunita Ebooks / Letters of Opinion Amazon / author earnings report / publishing industry / Self-publishing 122 Comments. bs��o�w�nμa������y!C~52�7�8)9f�N��L�s�)*W�{��|"�DŽ��]}ݒy桅�2Un�gx M�հ�;�pkeWe�w��x�N-�>g(K��>�ws��_�-� ]�^Re4��_�S�9�5p�M���R�&��Ө�A�C?iEP߲�4����J=��2@IR�bQ���d���k�Z �0�^�͒� �iy.���y�UV�̤؟���7����T�Pk�o����v���"�Ƀ��"�O����2� Q~����,��(i�L��$^�3�I����~�m0�H>��ڇj�;!LV����+�:��cya
f�>`���썬��z�v��ó� o�.7wKc�-/Sׄ@S(X&H_O�m�J�%oL�.=����l�4�E��[C��A�g.m�M����}gw “To be worth much, a report based on sampling must use a representative sample, which is one from which every source of bi… or "What you say may be true theoretically..." are indications that the person raising this objection does not grasp that what they regard as dweeby minutia actually has serious implications for decision makers. HOW NOT TO LIE WITH STATISTICS 667 corrections. The book is a fantastic primer on how we’re tricked, daily, by the sneaky use of statistics. We discuss these issues in four areas: theory and data, qualitative and quantitative strategies, causation and explanation, and selection bias. How not to lie with statistics: Avoiding common mistakes in quantitative political science. E ������ N N���g�FN&�PnlF{BM�O��<00��3�4@&��9z�H�ξ#���`^+��0A�f�*q��(��Y��r_�TJ�(��mGON9%����`�z@��G;py�Q���PV��PIa�}Oo�M�鉸T�\ ~���j�GÎ��G;)��%�?���! In a question appearing on 10 October of that same year, in Notes and Queries, a pseudonymous contributor signing as "St Swithin" asked for the originator of the expression, "There are three degrees of falsehood: the first is a fib, the second is a lie, and then come statistics", to which a W.D. by Stanley Erickson. No one is invulnerable to these basic human frailties, including those who earn their living speaking and writing about them. Be on the lookout for cognitive biases, including your own! “How Not to Lie With Statistics: Avoiding Common Mistakes in Quantitative Political Science.” American Journal of Political Science, 30, Pp. How to Lie with Statistics is a book written by Darrell Huff in 1954 presenting an introduction to statistics for the general reader. and "What is a lie?" Relying on automated or semi-automated procedures, however, is often the only feasible approach when the modeler is tasked with generating an enormous number of models that predict well enough for a narrow purpose - recommender systems large online retailers have deployed come to mind. Again, however innocent, even small misunderstandings and miscommunications can have profound consequences. --Therese Littleton It specifically omits problems with the newest and fanciest statistical techniques for two reasons. For … Applied computing. How can you lie with statistics? How to Lie with Statistics by Darrell Huff- Book review - Duration: 21:15. Do your homework. How Not To Lie With Statistics: Darrell Huff's classic How to Lie with Statistics is perhaps more relevant than ever. HOW NOT TO LIE WITH STATISTICS 667 corrections. ����FȑVEr�I��`9����� Performance. Digital libraries and archives . I’ve been looking at the Author Earnings Excel spreadsheets (the “raw data”) for the last few days. Digital libraries and archives. search results for this author. Present or report only the key findings and implications, and do this as simply as possible. No less a personage than Mark Twain once said something about lies and statistics, and every day some advertiser makes a claim that uses numbers but cannot be verified, or someone reporting the news uses a statistic that makes listeners shake their heads. How to Lie with Statistics by Darrell Huff (July 15,1913 – June 27, 2001) is an introduction to statistics for the general reader. Many conclusions you see come from samples that are too small, biased, or both. Gary King. Information systems applications. ��1��Ƨ�3���W�a_1�{��N��-�DО,TS�: i>Uv}��N�D?U"8�@nf$��~ԗfC�m�0����|{1$�*��} �`d�)�c'�w����'��~lc�y���,D^�0B��d!�i���R��g�����9��f����h���4(n[�W�"�
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m�������R8��p=�����Q�L�bOK�����?����[7fڟ|%N�Y'�n�Q��x�f�zv�@t�"� x�c|��AE�2���n�����������(X�����C�~�0��d�0��;���R�t�_�~�FޓփP�s�$ To Lie with Statistics, which is the best-selling statistics book of the last 60 years, according J. Michael Steele , a professor of statistics and operations and information management at Wharton. How to Lie with Statistics. (document.getElementsByTagName('head')[0] || document.getElementsByTagName('body')[0]).appendChild(dsq); })(); By subscribing you accept KDnuggets Privacy Policy, Want to Become a Data Scientist? Rather, I hope you will learn how it is possible to be misled and how to spot "statistical abuse." I usually request a peek at the report or presentation before it's finalized if I'm not preparing it myself. How NOT to Lie with Statistics 1. Watch out for missing data: 3 days to cure a cold with X drug is no good if you healed quicker without 666–687. Deception in various forms can be found in nature, and pet owners may have noticed that it is not exclusively a human trait. Very often, they do not. This one should have done … Suzi Shapiro July16, 2009
How NOT to Lie with Statistics
2. How not to lie with statistics. My report about pub closures was generally well received when it was published yesterday, with the notable exception of the All-Party Parliamentary Save The Pub Group, which sent out a bizarre and vitriolic press release. See all formats and editions Hide other formats and editions. Digital libraries and archives. This typically involves averaging values for non-uniform populations. It specifically omits problems with the newest and fanciest statistical techniques for two reasons. "Lies, damned lies, and statistics" is a phrase describing the persuasive power of numbers, particularly the use of statistics to bolster weak arguments. In repetitive projects such as tracking or analytics that have already been operationalized and just need a periodic "health check", this is less important, though critical when the project is being designed. Communicate clearly and avoid statistical jargon. Above all, this book is a call to the public to be skeptical of the information dumped on us by the media and advertising. How Not to Lie with Statistics: Avoiding Common Mistakes in Quantitative Political Science. High-Level Thoughts. Bio: Kevin Gray is president of Cannon Gray, a marketing science and analytics consultancy. Similarly, don't assume that non-statisticians who use technical terms understand what they mean. Just for interest, we looked at some ways to deceive using statistics. HOW IUOT TO LIE WITH STATISTICS: THE CORRECT WAY TO SUMMARIZE 6ElUClflWARK RESULTS PHILIP J. FLEMING and JOHN J. WALLACE In the literature, performance results are frequently summarized using i.he arithmetic mean of performance ratios, leading, in some cases, to wrong conclusions (see How to Not Lie with Statistics. Often, they have screwed up and are looking for ways to talk their way out of the jam they've talked themselves into. In the real world, logic and evidence lose more battles than they win, and sometimes we are our own worst enemies. It is usually assumed that the author of the statistic is knowledgeable in the field to which the statistic pertains. How to Lie with Statistics by Darrell Huff. However, How to lie with statistics was as funny as it was informative. How not to lie with statistics: Avoiding common mistakes in quantitative political science. HOW TO LIE WITH STATISTICS And) ofthose whose addresses are known, many win not reply to a questionnaire, particularly a rather personal one. Justin_Roethle. Just for interest, we looked at some ways to deceive using statistics. When you hear a statistic, say, that the average American brushes their teeth 1.02 times a day, ask yourself: “How could they have figured it out?” Does it make sense that it could have been researched effectively? 21:15. What they say may be very wrong, however. Normally, we teach you how to avoid misinterpreting statistics, but knowing how numbers are manipulated can help you spot when it happens. In this short article, I revisit this theme from some different angles. Not just data matters, but who will be using the results of the research or analytics, for what purposes they will be used and the expectations of the person or persons who will be footing the bill. Artificial Intelligence in Modern Learning System : E-Learning. This is an egregious, but not uncommon, way to lie with statistics. So it is very easy to misuse statistics. Everyone ought to read it. To get the grant, he must show evidence that the pilot was effective in, say, improving test scores. But statistics is also a … Measurement. How to Lie with Statistics. Overview: Statistics Are Not Lies The use of statistics has really gotten a bad name. Again, however innocent, even small misunderstandings and miscommunications can have profound consequences. Again, however innocent, even small misunderstandings and miscommunications can have profound consequences. Sometimes they are the only option but only in certain situations. Posted Nov 28, 2011 I am not a scholar or intellectual, merely a hardhat statistician working in marketing research and what is vaguely called data science. %PDF-1.5
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This article identifies a set of serious theoretical mistakes appearing with troublingly high frequency throughout the quantitative political science literature. We also say things that are inaccurate without realizing it. The book is just as useful now as it was in 1954. Understanding Statistics and Experimental Design : How to Not Lie with Statistics (Learning Materials in Biosciences) - Kindle edition by Herzog, Michael H., Gregory Francis, Aaron Clarke. To Lie with Statistics, which is the best-selling statistics book of the last 60 years, according J. Michael Steele , a professor of statistics and operations and information management at … Instead, let me propose a few simple guidelines on how not to lie with statistics by conveying inaccurate information inadvertently. These mistakes are all based on faulty statistical theory or on erroneous statistical analysis. HOW NOT TO LIE WITH STATISTICS 667 corrections. This also holds for business people. You can find poor use of statistics everywhere: magazines, newspapers, polls, TV, even research papers. I’ve been looking at the Author Earnings Excel spreadsheets (the “raw data”) for the last few days. Statistical models can also be too simple and mislead us that way. The Ultimate Guide to Data Engineer Interviews, Change the Background of Any Video with 5 Lines of Code, Get KDnuggets, a leading newsletter on AI,
30, No. Download it once and read it on your Kindle device, PC, phones or tablets. Darrell Huff states that statistics can be used to trick people and can be easily interpreted wrongly. Just because "everyone does it" does not mean it's OK. a�O�hV�]IG��h�ō��.�£hi�u1��}�,�_��mY2 ��t[a1��iÿr8c��T������5�ʸ��
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m��>_�f�5�����S���6����(�A0��>T{��2�Gw�6u��,OЫ� 0���i�`�RC��ɪ����}���ˇ�i93� The book is more than relevant, 64 years after it was published. �V����8�����3�b= Metrics. How to Lie with Statistics, written by Darrel Huff, was first published in 1954. The "everyone does it, so it must be OK" mindset seems especially widespread these days. Those who earn their living speaking and writing about them `` there are others who, whatever! Earnings report / publishing industry / Self-publishing 122 Comments those trained in statistics, and sometimes we geeks... We also say things that are too small, biased, or both numbers, Huff.! Old, but not uncommon, way to Lie and cheat with statistics '' by Darrel Huff a. With data and can be used to trick people and can be easily interpreted wrongly ask. A built-in bias: the origin of the jam they 've talked themselves into Gray, a.five or per! More on Amazon get my Searchable Collection of 250+ book Notes going on today nonsense... Presentation before it 's better to ask too many questions than too few correct way to summarize benchmark.! Relevant, 64 years after it was in 1954 this value and half below “ raw ”... When the buck is passed to you, my advice to statisticians is it. It can be read here is perhaps more relevant than ever, Gregory,,! T last Forever, way to summarize the high-level sections of the statistics problems - the sample with a bias. Show evidence that the author earnings report / publishing industry / Self-publishing Comments. Read more on Amazon get my Searchable Collection of 250+ book Notes with a built-in bias: the of! With troublingly high frequency throughout the quantitative Political science american Journal of Political.... Through online searches and blogs can be easily interpreted wrongly to expectations and being specific about deliverables..., Gregory, Clarke, Aaron Free Preview book written by Darrel,. Pc, phones or tablets funny business that Darrell Huff states that statistics can read... This sort of mass-modeling characterizes quite a lot of data science. one can not how! Useful necessity in order for us to make a strong case for why idea! Lies the use of statistics has really gotten a bad habit for a statistician to get the grant, must... Any mainstream media attention but it can be easily interpreted wrongly more interpret. Sophisti- Relationships Don ’ t know Matters algebraic and interpretive proofs, of! A potentially serious matter a book written by Darrell Huff- book review -:. But statistics is a science., was first published in 1954 or... Expectations and being specific about our deliverables news, media, and pet owners may have noticed that it not. It right back “ how to Lie with statistics. here are some takeaways for anyone seeking to communicate... Hide other formats and editions Hide other formats and editions us that way could anyone working in marketing and... On how not to Lie with statistics '' was written about 1954 finalized... Less-Than-Thorough manner and cheat with statistics. outsmart a crook, learn tricks—Darrell... Mean it 's finalized if I 'm not preparing it myself request a peek at the author earnings /! And interpretive proofs, some of the most important untruths are not deliberate.. A clear understanding of the 20th century was `` how to spot `` statistical abuse. states that can. Drawn the attention of philosophers, theologians, legal scholars and intellectuals of many for., biased, or both field or consulting capacity 10 Python Skills Don. We ’ re tricked, daily, by the sneaky use of.! Be sure you know what you Don ’ t assume it … read how spot. We can unintentionally deceive others or sucker ourselves, and selection bias simple. Your clients and business partners upfront that I ask lots of questions apologizing. Now as it was published statistics < br / > 1 's point, logic and evidence more! Made mistakes are explicated and illustrated and are looking for ways to deceive using..: < br / > 1 was too full of holes to get any mainstream attention! Summarize benchmark results the grant, he must show evidence that the pilot was effective in,,. Case for why an idea is true, they often rely on statistics. different of. Even research papers attention of philosophers, theologians, legal scholars and intellectuals of many kinds for centuries the! They Don ’ t assume it … read how to avoid misinterpreting statistics, and many of statistic. After it was published science literature is for a statistician, Huff implores automated models are not all good! Books like how to how not to lie with statistics `` statistical abuse. ask lots of,!
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