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Om författaren

David J. Hand is emeritus professor of mathematics and senior research investigator at Imperial College London. His many books include Statistics: A Very Short Introduction.

Inkluderar namnet: D. J. Hand

Verk av David J. Hand

Principles of Data Mining (2001) 86 exemplar
Dark Data (2020) 55 exemplar
Biplots (1995) 2 exemplar

Associerade verk

Intelligent Data Analysis (1999) — Redaktör, vissa utgåvor73 exemplar

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Allmänna fakta

Andra namn
HAND, David J.
Födelsedag
1950
Kön
male
Yrken
statistician
Kort biografi
rofessor David Hand is Senior Research Investigator and Emeritus Professor of Mathematics at Imperial College, London, where he formerly held the Chair in Statistics. He is also Chief Scientific Advisor to Winton Capital Management. He is a Fellow of the British Academy, and an Honorary Fellow of the Institute of Actuaries, and has served (twice) as President of the Royal Statistical Society. He is a non-executive director of the UK Statistics Authority, and is Chair of the Board of the UK Administrative Data Research Network. He has published 300 scientific papers and 28 books, including Principles of Data Mining, Information Generation, Measurement Theory and Practice, The Improbability Principle, and The Wellbeing of Nations. In 2002 he was awarded the Guy Medal of the Royal Statistical Society, and in 2012 he and his research group won the Credit Collections and Risk Award for Contributions to the Credit Industry. He was awarded the George Box Medal in 2016. In 2013 he was made OBE for services to research and innovation.
http://www.imperial.ac.uk/people/d.j....

Medlemmar

Recensioner

Het Onwaarschijnlijkheidsprincipe is een interessant boek dat laat zien dat de kans op een buitengewoon zeldzame gebeurtenis helemaal zo klein niet is. Sterker nog, het is juist heel logisch dat er vaak iets onalledaags gebeurt, zo illustreren de vijf wetten van onwaarschijnlijkheid ons. Zat Taleb er dan naast, en is zijn Black Swan helemaal niet zo’n “highly impropable event”?

Zo eenvoudig is het nu ook weer niet en dat past overigens prima bij dit boek. Het leest makkelijk weg maar is tegelijkertijd taaie stof. Steeds als ik een hoofdstuk uit had vroeg ik me af wat ik er nu eigenlijk van onthouden had en wat ik er mee kan in de praktijk. Dat laatste lees je in de laatste paragraaf van de bespreking op mijn boekenblog https://www.rizoomes.nl/boekenblog/… (mer)
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Rizoomes | 5 andra recensioner | Feb 25, 2024 |
Helped me understand even better than before, how not everything happens for a reason. Or, how the reasons, when there are reasons for an event, may be so varied and contingent, that we can never expect to know all of them.
 
Flaggad
mykl-s | 5 andra recensioner | May 29, 2023 |
Langdradig boek. Alleen hoofdstuk "Life, the Universe and everything" over evolutie theorie en het ontstaan van het heelal, of meer specifiek onze aarde, zijn interessant.
 
Flaggad
gerrit-anne | 5 andra recensioner | Dec 17, 2019 |
Wierd typo: the author asserts that journeys that would have taken days w/out a car, take but minutes w/ the car. He meant "hours", and the editor should have caught it. Also, "slip over" was maybe intended to be "fall over" or just "slip", unless that is an Anglicism unknown to me.

1. Surrounded by Statistics:
This is really just an introduction to the introduction.

2. Simple Descriptions
"ordinal", "ratio", "absolute" scale. I do not know that I have ever cared.
Summary numbers: the mean, the median, and the mode. There is the range, which is a measure of dispersion. Combined with the mean and the median, it should tell you something. It would be nice to write a program that would generate graphs of the distribution of values given the number of values, the range, the mean, and the median. It would be fun to under specify, too, so that, given only the mean, you could show the variety. There is also the standard deviation, and you could play the same trick with that. We can subdivide the data using quantiles, like the median, only with smaller sections.

3. Collecting Good Data
"observational" vs. "experimental" studies. Sampling the data: "sampling frame", "stratified random sampling" and "clustered random sampling". If we just want to find the average of some value over a total population we can sample and, the author argues, it is the absolute size of the sample rather than the relative size that matters.

4. Probability
"subjective", "frequentist", and "classical". I guess I would call classical "formalist". The cumulative probability distribution graph is drawn as continuous. But I looked on Wikipedia and that is not a necessary property. It is, however, a cadlag function. That makes sense, and I like it better. The probability density function doesn't convey information by checking one particular point, but rather by finding the area under the curve between two points. Wikipedia has a nice graphic showing the relationship of the median, mean, and mode to the probability density function. There is also a probability mass function, useful for representing probabilities of continuous random variables. Comparison of distributions: Bernoulli, binomial extends Bernoulli over multiple trials. The Poisson distribution, according to this author, is useful if the number of trials is unlimited, but I thought that was true of the binomial as well. For continuous variables, we can have the "uniform", "exponential", or "normal" distributions.
… (mer)
 
Flaggad
themulhern | 3 andra recensioner | Sep 14, 2019 |

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Statistik

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