A Valid Alternative to #Correlation for Rel. Data
http://journals.PLoS.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004075 Illustrates how r fails on simple expression expts HT @mason_lab
Posts Tagged ‘stats’
Proportionality: A Valid Alternative to Correlation for Relative Data
June 12, 2017Nullius in verba: A crash course in understanding numbers | The Economist
February 18, 2017Nullius in verba: A crash course in understanding numbers | The Economist
about:
A Field Guide to Lies and Statistics. By Daniel Levitin. Dutton; 292 pages; $28. Viking; £14.99.
https://www.amazon.com/Field-Guide-Lies-Statistics-Neuroscientist/dp/0241239990/ref=tmm_hrd_swatch_0?_encoding=UTF8&qid=1487476465&sr=8-1
Similar to:
How statistics lost their power – and why we should fear what comes next | William Davies | Politics | Th e Guardian
January 30, 2017How stats lost their power via @alexvespi
https://www.theguardian.com/politics/2017/jan/19/crisis-of-statistics-big-data-democracy Death of #DataScience in a “post-truth” world; anecdotes v elitist numbers
for those cold, lonely winter evenings…
July 24, 2016Guess the correlation http://guessthecorrelation.com/ Perhaps a useful sanity check for data from published papers. It’s so easy to fool oneself.
How does multiple testing correction work?
June 13, 2016How does multiple-testing correction work
http://www.nature.com/nbt/journal/v27/n12/abs/nbt1209-1135.html Intuition for teaching: genome-wide error rate on a single gene v family
Spurious Correlations
January 25, 2016.@fionabrinkman @BioMickWatson @iddux Spurious Correlations
(http://tylervigen.com/spurious-correlations) related to Stat Frankenstein (https://twitter.com/markgerstein/status/689478730343837696)
At Nearly 90, ‘Super Bowl’ Stock Analyst has a streak going – WSJ
January 18, 2016SuperBowl Stock Analyst has a streak http://www.wsj.com/articles/at-nearly-90-super-bowl-stock-analyst-has-a-streak-going-1452482753 #Statistical Frankenstein concept from Wall Street perhaps useful for genomics
10 types of regressions. Which one to use?
December 8, 201510 types of #regressions. Which one to use?
http://www.datasciencecentral.com/forum/topics/10-types-of-regressions-which-one-to-use Pitfalls of common approaches, eg linear or logistic via @KirkDBorne
IBM Research: Preserving Validity in Adaptive Data Analysis
September 23, 2015Preserving Validity in Adaptive Data Analysis http://ibmresearchnews.blogspot.com/2015/08/preserving-validity-in-adaptive-data_6.html Using differential #privacy for correct #stats even w/ test-set reuse
QT:{{"
“A common next step would be to use the least-squares linear regression to check whether a simple linear combination of the three strongly correlated foods can predict the grade. It turns out that a little combination goes a long way: we discover that a linear combination of the three selected foods can explain a significant fraction of variance in the grade (plotted below). The regression analysis also reports that the p-value of this result is 0.00009 meaning that the probability of this happening purely by chance is less than 1 in 10,000.
Recall that no relationship exists in the true data distribution, so this discovery is clearly false. This spurious effect is known to experts as Freedman’s paradox. It arises since the variables (foods) used in the regression were chosen using the data itself.
…
We found that challenges of adaptivity can be addressed using techniques developed for privacy-preserving data analysis. These techniques rely on the notion of differential privacy that guarantees that the data analysis is not too sensitive to the data of any single individual. We rigorously demonstrated that ensuring differential privacy of an analysis also guarantees that the findings will be statistically valid. We then also developed additional approaches to the problem based on a new way to measure how much information an analysis reveals about a dataset.
The Thresholdout Algorithm
Using our new approach we designed an algorithm, called Thresholdout, that allows an analyst to reuse the holdout set of data for validating a large number of results, even when those results are produced by an adaptive analysis.
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Science Isn’t Broken | FiveThirtyEight
August 22, 2015Science Isn’t Broken by @cragcrest
http://fivethirtyeight.com/features/science-isnt-broken Great (but cynical) description of “p-hacking” & “researcher degrees of freedom”
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