nhaliday + acm + biodet   7

Pearson correlation coefficient - Wikipedia
https://en.wikipedia.org/wiki/Coefficient_of_determination
what does this mean?: https://twitter.com/GarettJones/status/863546692724858880
deleted but it was about the Pearson correlation distance: 1-r
I guess it's a metric

https://en.wikipedia.org/wiki/Explained_variation

http://infoproc.blogspot.com/2014/02/correlation-and-variance.html
A less misleading way to think about the correlation R is as follows: given X,Y from a standardized bivariate distribution with correlation R, an increase in X leads to an expected increase in Y: dY = R dX. In other words, students with +1 SD SAT score have, on average, roughly +0.4 SD college GPAs. Similarly, students with +1 SD college GPAs have on average +0.4 SAT.

this reminds me of the breeder's equation (but it uses r instead of h^2, so it can't actually be the same)

https://www.reddit.com/r/slatestarcodex/comments/631haf/on_the_commentariat_here_and_why_i_dont_think_i/dfx4e2s/
stats  science  hypothesis-testing  correlation  metrics  plots  regression  wiki  reference  nibble  methodology  multi  twitter  social  discussion  best-practices  econotariat  garett-jones  concept  conceptual-vocab  accuracy  causation  acm  matrix-factorization  todo  explanation  yoga  hsu  street-fighting  levers  🌞  2014  scitariat  variance-components  meta:prediction  biodet  s:**  mental-math  reddit  commentary  ssc  poast  gwern  data-science  metric-space  similarity  measure  dependence-independence 
may 2017 by nhaliday
Information Processing: Assortative mating, regression and all that: offspring IQ vs parental midpoint
Assuming parental midpoint of n SD above the population average, the kids' IQ will be normally distributed about a mean which is around +.6n with residual SD of about 12 points. (The .6 could actually be anywhere in the range (.5, .7), but the SD doesn't vary much from choice of empirical inputs.)

possible to calculate the residual variance from first principles?

Some data on regression: http://infoproc.blogspot.com/2010/10/some-data-on-regression.html
hsu  parenting  iq  regression-to-mean  street-fighting  explanation  methodology  assortative-mating  scitariat  variance-components  biodet  nibble  behavioral-gen  multi  data  stories  education  acm 
november 2016 by nhaliday

bundles : academeacmframe

related tags

accuracy  acm  analysis  applications  article  assortative-mating  bayesian  behavioral-gen  benchmarks  best-practices  bio  biodet  bioinformatics  calculation  causation  commentary  compressed-sensing  concentration-of-measure  concept  conceptual-vocab  confidence  confounding  correlation  data  data-science  dependence-independence  discussion  distribution  econotariat  education  enhancement  estimate  expectancy  explanation  exposition  extrema  faq  garett-jones  GCTA  genetics  genomics  graphical-models  graphs  GWAS  gwern  GxE  hsu  hypothesis-testing  ideas  iidness  interdisciplinary  iq  latent-variables  lecture-notes  levers  linear-models  machine-learning  magnitude  matrix-factorization  measure  mental-math  meta:prediction  methodology  metric-space  metrics  ML-MAP-E  model-class  models  monte-carlo  multi  nibble  nonlinearity  orders  org:mat  outliers  papers  parenting  pdf  plots  poast  pop-structure  population-genetics  preprint  probability  reddit  reference  regression  regression-to-mean  regularization  s:**  scaling-up  science  scitariat  selection  similarity  simulation  social  sparsity  spearhead  ssc  stanford  stat-power  state-of-art  stats  stories  street-fighting  study  tails  tidbits  tightness  todo  twin-study  twitter  variance-components  wiki  yoga  🌞 

Copy this bookmark:



description:


tags: