nhaliday + methodology   454

Lindy effect - Wikipedia
The Lindy effect is a theory that the future life expectancy of some non-perishable things like a technology or an idea is proportional to their current age, so that every additional period of survival implies a longer remaining life expectancy.[1] Where the Lindy effect applies, mortality rate decreases with time. In contrast, living creatures and mechanical things follow a bathtub curve where, after "childhood", the mortality rate increases with time. Because life expectancy is probabilistically derived, a thing may become extinct before its "expected" survival. In other words, one needs to gauge both the age and "health" of the thing to determine continued survival.
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4 weeks ago by nhaliday
Why read old philosophy? | Meteuphoric
(This story would suggest that in physics students are maybe missing out on learning the styles of thought that produce progress in physics. My guess is that instead they learn them in grad school when they are doing research themselves, by emulating their supervisors, and that the helpfulness of this might partially explain why Nobel prizewinner advisors beget Nobel prizewinner students.)

The story I hear about philosophy—and I actually don’t know how much it is true—is that as bits of philosophy come to have any methodological tools other than ‘think about it’, they break off and become their own sciences. So this would explain philosophy’s lone status in studying old thinkers rather than impersonal methods—philosophy is the lone ur-discipline without impersonal methods but thinking.

This suggests a research project: try summarizing what Aristotle is doing rather than Aristotle’s views. Then write a nice short textbook about it.
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june 2018 by nhaliday
Is the human brain analog or digital? - Quora
The brain is neither analog nor digital, but works using a signal processing paradigm that has some properties in common with both.
 
Unlike a digital computer, the brain does not use binary logic or binary addressable memory, and it does not perform binary arithmetic. Information in the brain is represented in terms of statistical approximations and estimations rather than exact values. The brain is also non-deterministic and cannot replay instruction sequences with error-free precision. So in all these ways, the brain is definitely not "digital".
 
At the same time, the signals sent around the brain are "either-or" states that are similar to binary. A neuron fires or it does not. These all-or-nothing pulses are the basic language of the brain. So in this sense, the brain is computing using something like binary signals. Instead of 1s and 0s, or "on" and "off", the brain uses "spike" or "no spike" (referring to the firing of a neuron).
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april 2018 by nhaliday
Who We Are | West Hunter
I’m going to review David Reich’s new book, Who We Are and How We Got Here. Extensively: in a sense I’ve already been doing this for a long time. Probably there will be a podcast. The GoFundMe link is here. You can also send money via Paypal (Use the donate button), or bitcoins to 1Jv4cu1wETM5Xs9unjKbDbCrRF2mrjWXr5. In-kind donations, such as orichalcum or mithril, are always appreciated.

This is the book about the application of ancient DNA to prehistory and history.

height difference between northern and southern europeans: https://westhunt.wordpress.com/2018/03/29/who-we-are-1/
mixing, genocide of males, etc.: https://westhunt.wordpress.com/2018/03/29/who-we-are-2-purity-of-essence/
rapid change in polygenic traits (appearance by Kevin Mitchell and funny jab at Brad Delong ("regmonkey")): https://westhunt.wordpress.com/2018/03/30/rapid-change-in-polygenic-traits/
schiz, bipolar, and IQ: https://westhunt.wordpress.com/2018/03/30/rapid-change-in-polygenic-traits/#comment-105605
Dan Graur being dumb: https://westhunt.wordpress.com/2018/04/02/the-usual-suspects/
prediction of neanderthal mixture and why: https://westhunt.wordpress.com/2018/04/03/who-we-are-3-neanderthals/
New Guineans tried to use Denisovan admixture to avoid UN sanctions (by "not being human"): https://westhunt.wordpress.com/2018/04/04/who-we-are-4-denisovans/
also some commentary on decline of Out-of-Africa, including:
"Homo Naledi, a small-brained homonin identified from recently discovered fossils in South Africa, appears to have hung around way later that you’d expect (up to 200,000 years ago, maybe later) than would be the case if modern humans had occupied that area back then. To be blunt, we would have eaten them."

Live Not By Lies: https://westhunt.wordpress.com/2018/04/08/live-not-by-lies/
Next he slams people that suspect that upcoming genetic genetic analysis will, in most cases, confirm traditional stereotypes about race – the way the world actually looks.

The people Reich dumps on are saying perfectly reasonable things. He criticizes Henry Harpending for saying that he’d never seen an African with a hobby. Of course, Henry had actually spent time in Africa, and that’s what he’d seen. The implication is that people in Malthusian farming societies – which Africa was not – were selected to want to work, even where there was no immediate necessity to do so. Thus hobbies, something like a gerbil running in an exercise wheel.

He criticized Nicholas Wade, for saying that different races have different dispositions. Wade’s book wasn’t very good, but of course personality varies by race: Darwin certainly thought so. You can see differences at birth. Cover a baby’s nose with a cloth: Chinese and Navajo babies quietly breathe through their mouth, European and African babies fuss and fight.

Then he attacks Watson, for asking when Reich was going to look at Jewish genetics – the kind that has led to greater-than-average intelligence. Watson was undoubtedly trying to get a rise out of Reich, but it’s a perfectly reasonable question. Ashkenazi Jews are smarter than the average bear and everybody knows it. Selection is the only possible explanation, and the conditions in the Middle ages – white-collar job specialization and a high degree of endogamy, were just what the doctor ordered.

Watson’s a prick, but he’s a great prick, and what he said was correct. Henry was a prince among men, and Nick Wade is a decent guy as well. Reich is totally out of line here: he’s being a dick.

Now Reich may be trying to burnish his anti-racist credentials, which surely need some renewal after having pointing out that race as colloquially used is pretty reasonable, there’s no reason pops can’t be different, people that said otherwise ( like Lewontin, Gould, Montagu, etc. ) were lying, Aryans conquered Europe and India, while we’re tied to the train tracks with scary genetic results coming straight at us. I don’t care: he’s being a weasel, slandering the dead and abusing the obnoxious old genius who laid the foundations of his field. Reich will also get old someday: perhaps he too will someday lose track of all the nonsense he’s supposed to say, or just stop caring. Maybe he already has… I’m pretty sure that Reich does not like lying – which is why he wrote this section of the book (not at all logically necessary for his exposition of the ancient DNA work) but the required complex juggling of lies and truth required to get past the demented gatekeepers of our society may not be his forte. It has been said that if it was discovered that someone in the business was secretly an android, David Reich would be the prime suspect. No Talleyrand he.

https://westhunt.wordpress.com/2018/04/12/who-we-are-6-the-americas/
The population that accounts for the vast majority of Native American ancestry, which we will call Amerinds, came into existence somewhere in northern Asia. It was formed from a mix of Ancient North Eurasians and a population related to the Han Chinese – about 40% ANE and 60% proto-Chinese. Is looks as if most of the paternal ancestry was from the ANE, while almost all of the maternal ancestry was from the proto-Han. [Aryan-Transpacific ?!?] This formation story – ANE boys, East-end girls – is similar to the formation story for the Indo-Europeans.

https://westhunt.wordpress.com/2018/04/18/who-we-are-7-africa/
In some ways, on some questions, learning more from genetics has left us less certain. At this point we really don’t know where anatomically humans originated. Greater genetic variety in sub-Saharan African has been traditionally considered a sign that AMH originated there, but it possible that we originated elsewhere, perhaps in North Africa or the Middle East, and gained extra genetic variation when we moved into sub-Saharan Africa and mixed with various archaic groups that already existed. One consideration is that finding recent archaic admixture in a population may well be a sign that modern humans didn’t arise in that region ( like language substrates) – which makes South Africa and West Africa look less likely. The long-continued existence of homo naledi in South Africa suggests that modern humans may not have been there for all that long – if we had co-existed with homo naledi, they probably wouldn’t lasted long. The oldest known skull that is (probably) AMh was recently found in Morocco, while modern humans remains, already known from about 100,000 years ago in Israel, have recently been found in northern Saudi Arabia.

While work by Nick Patterson suggests that modern humans were formed by a fusion between two long-isolated populations, a bit less than half a million years ago.

So: genomics had made recent history Africa pretty clear. Bantu agriculuralists expanded and replaced hunter-gatherers, farmers and herders from the Middle East settled North Africa, Egypt and northeaat Africa, while Nilotic herdsmen expanded south from the Sudan. There are traces of earlier patterns and peoples, but today, only traces. As for questions back further in time, such as the origins of modern humans – we thought we knew, and now we know we don’t. But that’s progress.

https://westhunt.wordpress.com/2018/04/18/reichs-journey/
David Reich’s professional path must have shaped his perspective on the social sciences. Look at the record. He starts his professional career examining the role of genetics in the elevated prostate cancer risk seen in African-American men. Various social-science fruitcakes oppose him even looking at the question of ancestry ( African vs European). But they were wrong: certain African-origin alleles explain the increased risk. Anthropologists (and human geneticists) were sure (based on nothing) that modern humans hadn’t interbred with Neanderthals – but of course that happened. Anthropologists and archaeologists knew that Gustaf Kossina couldn’t have been right when he said that widespread material culture corresponded to widespread ethnic groups, and that migration was the primary explanation for changes in the archaeological record – but he was right. They knew that the Indo-European languages just couldn’t have been imposed by fire and sword – but Reich’s work proved them wrong. Lots of people – the usual suspects plus Hindu nationalists – were sure that the AIT ( Aryan Invasion Theory) was wrong, but it looks pretty good today.

Some sociologists believed that caste in India was somehow imposed or significantly intensified by the British – but it turns out that most jatis have been almost perfectly endogamous for two thousand years or more…

It may be that Reich doesn’t take these guys too seriously anymore. Why should he?

varnas, jatis, aryan invastion theory: https://westhunt.wordpress.com/2018/04/22/who-we-are-8-india/

europe and EEF+WHG+ANE: https://westhunt.wordpress.com/2018/05/01/who-we-are-9-europe/

https://www.nationalreview.com/2018/03/book-review-david-reich-human-genes-reveal-history/
The massive mixture events that occurred in the recent past to give rise to Europeans and South Asians, to name just two groups, were likely “male mediated.” That’s another way of saying that men on the move took local women as brides or concubines. In the New World there are many examples of this, whether it be among African Americans, where most European ancestry seems to come through men, or in Latin America, where conquistadores famously took local women as paramours. Both of these examples are disquieting, and hint at the deep structural roots of patriarchal inequality and social subjugation that form the backdrop for the emergence of many modern peoples.
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march 2018 by nhaliday
Frontiers | Can We Validate the Results of Twin Studies? A Census-Based Study on the Heritability of Educational Achievement | Genetics
As for most phenotypes, the amount of variance in educational achievement explained by SNPs is lower than the amount of additive genetic variance estimated in twin studies. Twin-based estimates may however be biased because of self-selection and differences in cognitive ability between twins and the rest of the population. Here we compare twin registry based estimates with a census-based heritability estimate, sampling from the same Dutch birth cohort population and using the same standardized measure for educational achievement. Including important covariates (i.e., sex, migration status, school denomination, SES, and group size), we analyzed 893,127 scores from primary school children from the years 2008–2014. For genetic inference, we used pedigree information to construct an additive genetic relationship matrix. Corrected for the covariates, this resulted in an estimate of 85%, which is even higher than based on twin studies using the same cohort and same measure. We therefore conclude that the genetic variance not tagged by SNPs is not an artifact of the twin method itself.
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december 2017 by nhaliday
galaxy - How do astronomers estimate the total mass of dust in clouds and galaxies? - Astronomy Stack Exchange
Dust absorbs stellar light (primarily in the ultraviolet), and is heated up. Subsequently it cools by emitting infrared, "thermal" radiation. Assuming a dust composition and grain size distribution, the amount of emitted IR light per unit dust mass can be calculated as a function of temperature. Observing the object at several different IR wavelengths, a Planck curve can be fitted to the data points, yielding the dust temperature. The more UV light incident on the dust, the higher the temperature.

The result is somewhat sensitive to the assumptions, and thus the uncertainties are sometimes quite large. The more IR data points obtained, the better. If only one IR point is available, the temperature cannot be calculated. Then there's a degeneracy between incident UV light and the amount of dust, and the mass can only be estimated to within some orders of magnitude (I think).
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december 2017 by nhaliday
How do you measure the mass of a star? (Beginner) - Curious About Astronomy? Ask an Astronomer
Measuring the mass of stars in binary systems is easy. Binary systems are sets of two or more stars in orbit about each other. By measuring the size of the orbit, the stars' orbital speeds, and their orbital periods, we can determine exactly what the masses of the stars are. We can take that knowledge and then apply it to similar stars not in multiple systems.

We also can easily measure the luminosity and temperature of any star. A plot of luminocity versus temperature for a set of stars is called a Hertsprung-Russel (H-R) diagram, and it turns out that most stars lie along a thin band in this diagram known as the main Sequence. Stars arrange themselves by mass on the Main Sequence, with massive stars being hotter and brighter than their small-mass bretheren. If a star falls on the Main Sequence, we therefore immediately know its mass.

In addition to these methods, we also have an excellent understanding of how stars work. Our models of stellar structure are excellent predictors of the properties and evolution of stars. As it turns out, the mass of a star determines its life history from day 1, for all times thereafter, not only when the star is on the Main Sequence. So actually, the position of a star on the H-R diagram is a good indicator of its mass, regardless of whether it's on the Main Sequence or not.
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december 2017 by nhaliday
Land, history or modernization? Explaining ethnic fractionalization: Ethnic and Racial Studies: Vol 38, No 2
Ethnic fractionalization (EF) is frequently used as an explanatory tool in models of economic development, civil war and public goods provision. However, if EF is endogenous to political and economic change, its utility for further research diminishes. This turns out not to be the case. This paper provides the first comprehensive model of EF as a dependent variable.
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december 2017 by nhaliday
microeconomics - Partial vs. general equilibrium - Economics Stack Exchange
The main difference between partial and general equilibrium models is, that partial equilibrium models assume that what happens on the market one wants to analyze has no effect on other markets.
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november 2017 by nhaliday
Use and Interpretation of LD Score Regression
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies: https://sci-hub.bz/10.1038/ng.3211
- Po-Ru Loh, Nick Patterson, et al.

https://www.biorxiv.org/content/biorxiv/early/2014/02/21/002931.full.pdf

Both polygenicity (i.e. many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield inflated distributions of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from bias and true signal from polygenicity. We have developed an approach that quantifies the contributions of each by examining the relationship between test statistics and linkage disequilibrium (LD). We term this approach LD Score regression. LD Score regression provides an upper bound on the contribution of confounding bias to the observed inflation in test statistics and can be used to estimate a more powerful correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of test statistic inflation in many GWAS of large sample size.

Supplementary Note: https://images.nature.com/original/nature-assets/ng/journal/v47/n3/extref/ng.3211-S1.pdf

An atlas of genetic correlations across human diseases
and traits: https://sci-hub.bz/10.1038/ng.3406

https://www.biorxiv.org/content/early/2015/01/27/014498.full.pdf

Supplementary Note: https://images.nature.com/original/nature-assets/ng/journal/v47/n11/extref/ng.3406-S1.pdf

https://github.com/bulik/ldsc
ldsc is a command line tool for estimating heritability and genetic correlation from GWAS summary statistics. ldsc also computes LD Scores.
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november 2017 by nhaliday
Ancient Admixture in Human History
- Patterson, Reich et al., 2012
Population mixture is an important process in biology. We present a suite of methods for learning about population mixtures, implemented in a software package called ADMIXTOOLS, that support formal tests for whether mixture occurred and make it possible to infer proportions and dates of mixture. We also describe the development of a new single nucleotide polymorphism (SNP) array consisting of 629,433 sites with clearly documented ascertainment that was specifically designed for population genetic analyses and that we genotyped in 934 individuals from 53 diverse populations. To illustrate the methods, we give a number of examples that provide new insights about the history of human admixture. The most striking finding is a clear signal of admixture into northern Europe, with one ancestral population related to present-day Basques and Sardinians and the other related to present-day populations of northeast Asia and the Americas. This likely reflects a history of admixture between Neolithic migrants and the indigenous Mesolithic population of Europe, consistent with recent analyses of ancient bones from Sweden and the sequencing of the genome of the Tyrolean “Iceman.”
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november 2017 by nhaliday
SEXUAL DIMORPHISM, SEXUAL SELECTION, AND ADAPTATION IN POLYGENIC CHARACTERS - Lande - 1980 - Evolution - Wiley Online Library
https://twitter.com/gcochran99/status/970758341990367232
https://archive.is/mcKvr
Lol, that's nothing, my biology teacher in high school told me sex differences couldn't evolve since all of us inherit 50% of genes from parents of both sexes. Being a raucous hispanic kid I burst out laughing, she was not pleased
--
Sex differences actually evolve more slowly because of that: something like 80 times more slowly.
...
Doesn't have that number, but in the same ballpark.

Sexual Dimorphism, Sexual Selection, And Adaptation In Polygenic Characters

Russell Lande

https://twitter.com/gcochran99/status/999189778867208193
https://archive.is/AR8FY
I believe it, because sex differences [ in cases where the trait is not sex-limited ] evolve far more slowly than other things, on the order of 100 times more slowly. Lande 1980: https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1558-5646.1980.tb04817.x

The deep past has a big vote in such cases.
...
as for the extent that women were voluntarily choosing mates 20k years ago, or 100k years ago - I surely don't know.

other time mentioned: https://pinboard.in/u:nhaliday/b:3a7c5b42dd50
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november 2017 by nhaliday
Global Evidence on Economic Preferences
- Benjamin Enke et al

This paper studies the global variation in economic preferences. For this purpose, we present the Global Preference Survey (GPS), an experimentally validated survey dataset of time preference, risk preference, positive and negative reciprocity, altruism, and trust from 80,000 individuals in 76 countries. The data reveal substantial heterogeneity in preferences across countries, but even larger within-country heterogeneity. Across individuals, preferences vary with age, gender, and cognitive ability, yet these relationships appear partly country specific. At the country level, the data reveal correlations between preferences and bio-geographic and cultural variables such as agricultural suitability, language structure, and religion. Variation in preferences is also correlated with economic outcomes and behaviors. Within countries and subnational regions, preferences are linked to individual savings decisions, labor market choices, and prosocial behaviors. Across countries, preferences vary with aggregate outcomes ranging from per capita income, to entrepreneurial activities, to the frequency of armed conflicts.

...

This paper explores these questions by making use of the core features of the GPS: (i) coverage of 76 countries that represent approximately 90 percent of the world population; (ii) representative population samples within each country for a total of 80,000 respondents, (iii) measures designed to capture time preference, risk preference, altruism, positive reciprocity, negative reciprocity, and trust, based on an ex ante experimental validation procedure (Falk et al., 2016) as well as pre-tests in culturally heterogeneous countries, (iv) standardized elicitation and translation techniques through the pre-existing infrastructure of a global polling institute, Gallup. Upon publication, the data will be made publicly available online. The data on individual preferences are complemented by a comprehensive set of covariates provided by the Gallup World Poll 2012.

...

The GPS preference measures are based on twelve survey items, which were selected in an initial survey validation study (see Falk et al., 2016, for details). The validation procedure involved conducting multiple incentivized choice experiments for each preference, and testing the relative abilities of a wide range of different question wordings and formats to predict behavior in these choice experiments. The particular items used to construct the GPS preference measures were selected based on optimal performance out of menus of alternative items (for details see Falk et al., 2016). Experiments provide a valuable benchmark for selecting survey items, because they can approximate the ideal choice situations, specified in economic theory, in which individuals make choices in controlled decision contexts. Experimental measures are very costly, however, to implement in a globally representative sample, whereas survey measures are much less costly.⁴ Selecting survey measures that can stand in for incentivized revealed preference measures leverages the strengths of both approaches.

The Preference Survey Module: A Validated Instrument for Measuring Risk, Time, and Social Preferences: http://ftp.iza.org/dp9674.pdf

Table 1: Survey items of the GPS

Figure 1: World maps of patience, risk taking, and positive reciprocity.
Figure 2: World maps of negative reciprocity, altruism, and trust.

Figure 3: Gender coefficients by country. For each country, we regress the respective preference on gender, age and its square, and subjective math skills, and plot the resulting gender coefficients as well as their significance level. In order to make countries comparable, each preference was standardized (z-scores) within each country before computing the coefficients.

Figure 4: Cognitive ability coefficients by country. For each country, we regress the respective preference on gender, age and its square, and subjective math skills, and plot the resulting coefficients on subjective math skills as well as their significance level. In order to make countries comparable, each preference was standardized (z-scores) within each country before computing the coefficients.

Figure 5: Age profiles by OECD membership.

Table 6: Pairwise correlations between preferences and geographic and cultural variables

Figure 10: Distribution of preferences at individual level.
Figure 11: Distribution of preferences at country level.

interesting digression:
D Discussion of Measurement Error and Within- versus Between-Country Variation
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october 2017 by nhaliday
Karl Pearson and the Chi-squared Test
Pearson's paper of 1900 introduced what subsequently became known as the chi-squared test of goodness of fit. The terminology and allusions of 80 years ago create a barrier for the modern reader, who finds that the interpretation of Pearson's test procedure and the assessment of what he achieved are less than straightforward, notwithstanding the technical advances made since then. An attempt is made here to surmount these difficulties by exploring Pearson's relevant activities during the first decade of his statistical career, and by describing the work by his contemporaries and predecessors which seem to have influenced his approach to the problem. Not all the questions are answered, and others remain for further study.

original paper: http://www.economics.soton.ac.uk/staff/aldrich/1900.pdf

How did Karl Pearson come up with the chi-squared statistic?: https://stats.stackexchange.com/questions/97604/how-did-karl-pearson-come-up-with-the-chi-squared-statistic
He proceeds by working with the multivariate normal, and the chi-square arises as a sum of squared standardized normal variates.

You can see from the discussion on p160-161 he's clearly discussing applying the test to multinomial distributed data (I don't think he uses that term anywhere). He apparently understands the approximate multivariate normality of the multinomial (certainly he knows the margins are approximately normal - that's a very old result - and knows the means, variances and covariances, since they're stated in the paper); my guess is that most of that stuff is already old hat by 1900. (Note that the chi-squared distribution itself dates back to work by Helmert in the mid-1870s.)

Then by the bottom of p163 he derives a chi-square statistic as "a measure of goodness of fit" (the statistic itself appears in the exponent of the multivariate normal approximation).

He then goes on to discuss how to evaluate the p-value*, and then he correctly gives the upper tail area of a χ212χ122 beyond 43.87 as 0.000016. [You should keep in mind, however, that he didn't correctly understand how to adjust degrees of freedom for parameter estimation at that stage, so some of the examples in his papers use too high a d.f.]
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october 2017 by nhaliday
Section 10 Chi-squared goodness-of-fit test.
- pf that chi-squared statistic for Pearson's test (multinomial goodness-of-fit) actually has chi-squared distribution asymptotically
- the gotcha: terms Z_j in sum aren't independent
- solution:
- compute the covariance matrix of the terms to be E[Z_iZ_j] = -sqrt(p_ip_j)
- note that an equivalent way of sampling the Z_j is to take a random standard Gaussian and project onto the plane orthogonal to (sqrt(p_1), sqrt(p_2), ..., sqrt(p_r))
- that is equivalent to just sampling a Gaussian w/ 1 less dimension (hence df=r-1)
QED
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october 2017 by nhaliday
self study - Looking for a good and complete probability and statistics book - Cross Validated
I never had the opportunity to visit a stats course from a math faculty. I am looking for a probability theory and statistics book that is complete and self-sufficient. By complete I mean that it contains all the proofs and not just states results.
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october 2017 by nhaliday
Why are children in the same family so different from one another? - PubMed - NCBI
- Plomin et al

The article has three goals: (1) To describe quantitative genetic methods and research that lead to the conclusion that nonshared environment is responsible for most environmental variation relevant to psychological development, (2) to discuss specific nonshared environmental influences that have been studied to date, and (3) to consider relationships between nonshared environmental influences and behavioral differences between children in the same family. The reason for presenting this article in BBS is to draw attention to the far-reaching implications of finding that psychologically relevant environmental influences make children in a family different from, not similar to, one another.
study  essay  article  survey  spearhead  psychology  social-psych  biodet  behavioral-gen  🌞  methodology  environmental-effects  signal-noise  systematic-ad-hoc  composition-decomposition  pdf  piracy  volo-avolo  developmental  iq  cog-psych  variance-components  GxE  nonlinearity  twin-study  personality  sib-study 
october 2017 by nhaliday
Social Animal House: The Economic and Academic Consequences of Fraternity Membership by Jack Mara, Lewis Davis, Stephen Schmidt :: SSRN
We exploit changes in the residential and social environment on campus to identify the economic and academic consequences of fraternity membership at a small Northeastern college. Our estimates suggest that these consequences are large, with fraternity membership lowering student GPA by approximately 0.25 points on the traditional four-point scale, but raising future income by approximately 36%, for those students whose decision about membership is affected by changes in the environment. These results suggest that fraternity membership causally produces large gains in social capital, which more than outweigh its negative effects on human capital for potential members. Alcohol-related behavior does not explain much of the effects of fraternity membership on either the human capital or social capital effects. These findings suggest that college administrators face significant trade-offs when crafting policies related to Greek life on campus.

- III. Methodology has details
- it's an instrumental variable method paper

Table 5: Fraternity Membership and Grades

Do High School Sports Build or Reveal Character?: http://ftp.iza.org/dp11110.pdf
We examine the extent to which participation in high school athletics has beneficial effects on future education, labor market, and health outcomes. Due to the absence of plausible instruments in observational data, we use recently developed methods that relate selection on observables with selection on unobservables to estimate bounds on the causal effect of athletics participation. We analyze these effects in the US separately for men and women using three different nationally representative longitudinal data sets that each link high school athletics participation with later-life outcomes. We do not find consistent evidence of individual benefits reported in many previous studies – once we have accounted for selection, high school athletes are no more likely to attend college, earn higher wages, or participate in the labor force. However, we do find that men (but not women) who participated in high school athletics are more likely to exercise regularly as adults. Nevertheless, athletes are no less likely to be obese.

Online Social Network Effects in Labor Markets: Evidence From Facebook's Entry into College Campuses: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3381938
My estimates imply that access to Facebook for 4 years of college causes a 2.7 percentile increase in a cohort's average earnings, relative to the earnings of other individuals born in the same year.

https://marginalrevolution.com/marginalrevolution/2019/05/might-facebook-boost-wages.html
What Clockwork_Prior said. I was a college freshman when facebook first made its appearance and so I know that facebook's entry/exit cannot be treated as a quasi-random with respect to earnings. Facebook began at harvard, then expanded to other ivy league schools + places like stanford/MIT/CMU, before expanding into a larger set of universities.

Presuming the author is using a differences-in-differences research design, the estimates would be biased as they would essentially be calculating averaging earnings difference between Elite schools and non elite schools. If the sample is just restricted to the period where schools were simply elite, the problem still exist because facebook originated at Harvard and this becomes a comparison of Harvard earnings v.s. other schools.
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september 2017 by nhaliday
Accurate Genomic Prediction Of Human Height | bioRxiv
Stephen Hsu's compressed sensing application paper

We construct genomic predictors for heritable and extremely complex human quantitative traits (height, heel bone density, and educational attainment) using modern methods in high dimensional statistics (i.e., machine learning). Replication tests show that these predictors capture, respectively, ~40, 20, and 9 percent of total variance for the three traits. For example, predicted heights correlate ~0.65 with actual height; actual heights of most individuals in validation samples are within a few cm of the prediction.

https://infoproc.blogspot.com/2017/09/accurate-genomic-prediction-of-human.html

http://infoproc.blogspot.com/2017/11/23andme.html
I'm in Mountain View to give a talk at 23andMe. Their latest funding round was $250M on a (reported) valuation of $1.5B. If I just add up the Crunchbase numbers it looks like almost half a billion invested at this point...

Slides: Genomic Prediction of Complex Traits

Here's how people + robots handle your spit sample to produce a SNP genotype:

https://drive.google.com/file/d/1e_zuIPJr1hgQupYAxkcbgEVxmrDHAYRj/view
study  bio  preprint  GWAS  state-of-art  embodied  genetics  genomics  compressed-sensing  high-dimension  machine-learning  missing-heritability  hsu  scitariat  education  🌞  frontier  britain  regression  data  visualization  correlation  phase-transition  multi  commentary  summary  pdf  slides  brands  skunkworks  hard-tech  presentation  talks  methodology  intricacy  bioinformatics  scaling-up  stat-power  sparsity  norms  nibble  speedometer  stats  linear-models  2017  biodet 
september 2017 by nhaliday
Of mice and men: why animal trial results don’t always translate to humans
It showed that of the most-cited animal studies in prestigious scientific journals, such as Nature and Cell, only 37% were replicated in subsequent human randomised trials and 18% were contradicted in human trials. It is safe to assume that less-cited animal studies in lesser journals would have an even lower strike rate.
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september 2017 by nhaliday
Caught in the act | West Hunter
The fossil record is sparse. Let me try to explain that. We have at most a few hundred Neanderthal skeletons, most in pretty poor shape. How many Neanderthals ever lived? I think their population varied in size quite a bit – lowest during glacial maxima, probably highest in interglacials. Their degree of genetic diversity suggests an effective population size of ~1000, but that would be dominated by the low points (harmonic average). So let’s say 50,000 on average, over their whole range (Europe, central Asia, the Levant, perhaps more). Say they were around for 300,000 years, with a generation time of 30 years – 10,000 generations, for a total of five hundred million Neanderthals over all time. So one in a million Neanderthals ends up in a museum: one every 20 generations. Low time resolution!

So if anatomically modern humans rapidly wiped out Neanderthals, we probably couldn’t tell. In much the same way, you don’t expect to find the remains of many dinosaurs killed by the Cretaceous meteor impact (at most one millionth of one generation, right?), or of Columbian mammoths killed by a wave of Amerindian hunters. Sometimes invaders leave a bigger footprint: a bunch of cities burning down with no rebuilding tells you something. But even when you know that population A completely replaced population B, it can be hard to prove that just how it happened. After all, population A could have all committed suicide just before B showed up. Stranger things have happened – but not often.
west-hunter  scitariat  discussion  ideas  data  objektbuch  scale  magnitude  estimate  population  sapiens  archaics  archaeology  pro-rata  history  antiquity  methodology  volo-avolo  measurement  pop-structure  density  time  frequency  apollonian-dionysian  traces  evidence 
september 2017 by nhaliday
Of Mice and Men | West Hunter
It’s not always easy figuring out how a pathogen causes disease. There is an example in mice for which the solution was very difficult, so difficult that we would probably have failed to discover the cause of a similarly obscure infectious disease in humans.

Mycoplasma pulmonis causes a chronic obstructive lung disease in mice, but it wasn’t easy to show this. The disease was first described in 1915, and by 1940, people began to suspect Mycoplasma pulmonis might be the cause. But then again, maybe not. It was often found in mice that seemed healthy. Pure cultures of this organism did not consistently produce lung disease – which means that it didn’t satisfy Koch’s postulates, in particular postulate 1 (The microorganism must be found in abundance in all organisms suffering from the disease, but should not be found in healthy organisms.) and postulate 3 (The cultured microorganism should cause disease when introduced into a healthy organism.).

Well, those postulates are not logic itself, but rather a useful heuristic. Koch knew that, even if lots of other people don’t.

This respiratory disease of mice is long-lasting, but slow to begin. It can take half a lifetime – a mouse lifetime, that is – and that made finding the cause harder. It required patience, which means I certainly couldn’t have done it.

Here’s how they solved it. You can raise germ-free mice. In the early 1970s, researchers injected various candidate pathogens into different groups of germ-free mice and waited to see which, if any, developed this chronic lung disease. It was Mycoplasma pulmonis , all right, but it had taken 60 years to find out.

It turned out that susceptibility differed between different mouse strains – genetic susceptibility was important. Co-infection with other pathogens affected the course of the disease. Microenvironmental details mattered – mainly ammonia in cages where the bedding wasn’t changed often enough. But it didn’t happen without that mycoplasma, which was a key causal link, something every engineer understands but many MDs don’t.

If there was a similarly obscure infectious disease of humans, say one that involved a fairly common bug found in both the just and the unjust, one that took decades for symptoms to manifest – would we have solved it? Probably not.

Cooties are everywhere.

gay germ search: https://westhunt.wordpress.com/2013/07/21/of-mice-and-men/#comment-15905
It’s hard to say, depends on how complicated the path of causation is. Assuming that I’m even right, of course. Some good autopsy studies might be fruitful – you’d look for microanatomical brain differences, as with nartcolepsy. Differences in gene expression, maybe. You could look for a pathogen – using the digital version of RDA (representational difference analysis), say on discordant twins. Do some old-fashioned epidemiology. Look for marker antibodies, signs of some sort of immunological event.

Do all of the above on gay rams – lots easier to get started, much less whining from those being vivisected.

Patrick Moore found the virus causing Kaposi’s sarcoma without any funding at all. I’m sure Peter Thiel could afford a serious try.
west-hunter  scitariat  discussion  ideas  reflection  analogy  model-organism  bio  disease  parasites-microbiome  medicine  epidemiology  heuristic  thick-thin  stories  experiment  track-record  intricacy  gotchas  low-hanging  🌞  patience  complex-systems  meta:medicine  multi  poast  methodology  red-queen  brain-scan  neuro  twin-study  immune  nature  gender  sex  sexuality  thiel  barons  gwern  stylized-facts  inference  apollonian-dionysian 
september 2017 by nhaliday
Demography of the Roman Empire - Wikipedia
There are few recorded population numbers for the whole of antiquity, and those that exist are often rhetorical or symbolic. Unlike the contemporaneous Han Dynasty, no general census survives for the Roman Empire. The late period of the Roman Republic provides a small exception to this general rule: serial statistics for Roman citizen numbers, taken from census returns, survive for the early Republic through the 1st century CE.[41] Only the figures for periods after the mid-3rd century BCE are reliable, however. Fourteen figures are available for the 2nd century BCE (from 258,318 to 394,736). Only four figures are available for the 1st century BCE, and are feature a large break between 70/69 BCE (910,000) and 28 BCE (4,063,000). The interpretation of the later figures—the Augustan censuses of 28 BCE, 8 BCE, and 14 CE—is therefore controversial.[42] Alternate interpretations of the Augustan censuses (such as those of E. Lo Cascio[43]) produce divergent population histories across the whole imperial period.[44]

Roman population size: the logic of the debate: https://www.princeton.edu/~pswpc/pdfs/scheidel/070706.pdf
- Walter Scheidel (cited in book by Vaclav Smil, "Why America is Not a New Rome")

Our ignorance of ancient population numbers is one of the biggest obstacles to our understanding of Roman history. After generations of prolific scholarship, we still do not know how many people inhabited Roman Italy and the Mediterranean at any given point in time. When I say ‘we do not know’ I do not simply mean that we lack numbers that are both precise and safely known to be accurate: that would surely be an unreasonably high standard to apply to any pre-modern society. What I mean is that even the appropriate order of magnitude remains a matter of intense dispute.

Historical urban community sizes: https://en.wikipedia.org/wiki/Historical_urban_community_sizes

World population estimates: https://en.wikipedia.org/wiki/World_population_estimates
As a general rule, the confidence of estimates on historical world population decreases for the more distant past. Robust population data only exists for the last two or three centuries. Until the late 18th century, few governments had ever performed an accurate census. In many early attempts, such as in Ancient Egypt and the Persian Empire, the focus was on counting merely a subset of the population for purposes of taxation or military service.[3] Published estimates for the 1st century ("AD 1") suggest an uncertainty of the order of 50% (estimates range between 150 and 330 million). Some estimates extend their timeline into deep prehistory, to "10,000 BC", i.e. the early Holocene, when world population estimates range roughly between one and ten million (with an uncertainty of up to an order of magnitude).[4][5]

Estimates for yet deeper prehistory, into the Paleolithic, are of a different nature. At this time human populations consisted entirely of non-sedentary hunter-gatherer populations, with anatomically modern humans existing alongside archaic human varieties, some of which are still ancestral to the modern human population due to interbreeding with modern humans during the Upper Paleolithic. Estimates of the size of these populations are a topic of paleoanthropology. A late human population bottleneck is postulated by some scholars at approximately 70,000 years ago, during the Toba catastrophe, when Homo sapiens population may have dropped to as low as between 1,000 and 10,000 individuals.[6][7] For the time of speciation of Homo sapiens, some 200,000 years ago, an effective population size of the order of 10,000 to 30,000 individuals has been estimated, with an actual "census population" of early Homo sapiens of roughly 100,000 to 300,000 individuals.[8]
history  iron-age  mediterranean  the-classics  demographics  fertility  data  europe  population  measurement  volo-avolo  estimate  wiki  reference  article  conquest-empire  migration  canon  scale  archaeology  multi  broad-econ  pdf  study  survey  debate  uncertainty  walter-scheidel  vaclav-smil  urban  military  economics  labor  time-series  embodied  health  density  malthus  letters  urban-rural  database  list  antiquity  medieval  early-modern  mostly-modern  time  sequential  MENA  the-great-west-whale  china  asia  sinosphere  occident  orient  japan  britain  germanic  gallic  summary  big-picture  objektbuch  confidence  sapiens  anthropology  methodology  farmers-and-foragers  genetics  genomics  chart 
august 2017 by nhaliday
All models are wrong - Wikipedia
Box repeated the aphorism in a paper that was published in the proceedings of a 1978 statistics workshop.[2] The paper contains a section entitled "All models are wrong but some are useful". The section is copied below.

Now it would be very remarkable if any system existing in the real world could be exactly represented by any simple model. However, cunningly chosen parsimonious models often do provide remarkably useful approximations. For example, the law PV = RT relating pressure P, volume V and temperature T of an "ideal" gas via a constant R is not exactly true for any real gas, but it frequently provides a useful approximation and furthermore its structure is informative since it springs from a physical view of the behavior of gas molecules.

For such a model there is no need to ask the question "Is the model true?". If "truth" is to be the "whole truth" the answer must be "No". The only question of interest is "Is the model illuminating and useful?".
thinking  metabuch  metameta  map-territory  models  accuracy  wire-guided  truth  philosophy  stats  data-science  methodology  lens  wiki  reference  complex-systems  occam  parsimony  science  nibble  hi-order-bits  info-dynamics  the-trenches  meta:science  physics  fluid  thermo  stat-mech  applicability-prereqs  theory-practice  elegance 
august 2017 by nhaliday
Divorce demography - Wikipedia
https://en.wikipedia.org/wiki/Divorce_in_the_United_States#Rates_of_divorce
https://psychcentral.com/lib/the-myth-of-the-high-rate-of-divorce/

Marriage update: less divorce, and less sex: https://familyinequality.wordpress.com/2017/04/14/marriage-update-less-divorce-and-less-sex/

Breaking Up Is Hard to Count: The Rise of Divorce in the United States, 1980–2010: https://link.springer.com/article/10.1007%2Fs13524-013-0270-9
Divorce rates have doubled over the past two decades among persons over age 35. Among the youngest couples, however, divorce rates are stable or declining. If current trends continue, overall age-standardized divorce rates could level off or even decline over the next few decades. We argue that the leveling of divorce among persons born since 1980 probably reflects the increasing selectivity of marriage.
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august 2017 by nhaliday
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