Search for tag: "variance"

6 Media

46:53 Why we still need to talk about diversity in… Why we still need to talk about diversity in Physics - Dr. Jess Wade	Why we still need to talk about diversity in Physics - Dr. Jess Wade Dr. Jess Wade is a physicist who, alongside being a postdoc researcher at Imperial College London in plastic electronics, campaigns tirelessly to increase diversity in physics. One of Nature's… observational astronomy lunch time voting theory facial recognition wikimedia uk sexual harassment long time gender bias single week empiricism science teachers sensory system engage young teaching huge impact huge amount primary school big thing subjective experience women in red diversity in stem effects gender balance skills specialist science big international equality cognition family law great book women scientists big impact b.b.c.neuropsychological assessment small amount school types big study social sciences half time theory of probability distributions mental health chemistry education wikipedia g.c.s.e.bigger variance gender gap minority backgrounds represented minority medical trials marriage majority–minority relations phenomenal people school equality won $3000000.00 careers in stem stem i.b.m.high school probability theory women in stem young girl 1516 year study physics u.k.big investigation community super super depressing school terminology decision theory small time p.b.s.big challenge absolutely massive peer review astronomical imaging diversity jess wade radio waves absolutely incredible academic career massachusetts institute of technology unconscious bias stem subjects equality and diversity cognitive science scientific community early career represented minority backgrounds represented minority groups award scheme women in science mit media young people women in physics education caption complete massive massive huge shortage mit i.q.women in chemistry bullying mental health support brilliant time representation persecution book inferior information systems science department huge huge nobel prize physics conscious bias From Ewan McAndrew 5 Months ago 1 likes 252 views 0 Publisher Ewan McAndrew - Wikimedian in Residence Licence Type Creative Commons - Attribution Share A Like Language English Date Created 30/01/2019
03:15 A Probilistic View A Probilistic View	A Probilistic View A probabilistic formulation of the linear model square probability regression analysis gaussian probabilistically general predicts regression caption complete annoyance probabilistic systems theory 2017 mosquito function iaml noise linear model theory of probability distributions equivalent statistical terminology component effects output estimate likelihood probability theory structure remember solution linear regression algorithms residuals variance problem From Nigel Goddard A year ago 0 likes 1,190 views 0 Licence Type Creative Commons - Attribution
09:16 Confidence Interval for Generalization Confidence Interval for Generalization	Confidence Interval for Generalization Confidence Interval for Generalization probability percent gaussian summary statistics measurement misclassified tomorrow caption complete theory of probability distributions test set question instance elementary algebra compute evaluation iaml data analysis statistical terminology number standard deviation total number unbiased estimate human communication future error probability theory error rate 100 times percent confidence interval future test true error rate future square root confidence interval variance distribution statistical deviation and dispersion minus effects From Nigel Goddard 2 Years ago 0 likes 1,470 views 0 Licence Type Creative Commons - Attribution
02:26 Example where Naive Bayes Fails Example where Naive Bayes Fails	Example where Naive Bayes Fails Example where Naive Bayes Fails weight independent problem height children caption complete variance positive differentiates iaml separate naive covariance effects attributes distinguish estimate difference class condition correlated black class points hopeless correlation situation distribution red class From Nigel Goddard 2 Years ago 1 likes 1,469 views 0 Licence Type Creative Commons - Attribution
07:37 Gaussian Naive Bayes Classifier Gaussian Naive Bayes Classifier	Gaussian Naive Bayes Classifier Gaussian Naive Bayes Classifier multiplying force probability number height effectively individual big number children caption complete weight specification question pretty iaml product plays set in new york city physical quantities statistical terminology histogram average child adult child libertarian theory small number probability theory individualism commerce compute remember legal terms political philosophy small variance model observation represented effects From Nigel Goddard 2 Years ago 2 likes 1,765 views 0 Licence Type Creative Commons - Attribution
03:09 Naive Bayes for Real-Valued Data Naive Bayes for Real-Valued Data	Naive Bayes for Real-Valued Data Naive Bayes for Real-Valued Data model probability number height elementary mathematics individual children caption complete theory of probability distributions weight training examples construct statistical deviation and dispersion observations probability theory centimeters iaml data analysis means statistical terminology estimation theory effects child estimate difference class individualism count quarter compute legal terms average adult prior summary statistics variance distribution estimation differentiate From Nigel Goddard 2 Years ago 0 likes 1,449 views 0 Licence Type Creative Commons - Attribution

the university of edinburgh

University affiliations

The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336, VAT Registration Number GB 592 9507 00, and is acknowledged by the UK authorities as a “Recognised body” which has been granted degree awarding powers.

Unless explicitly stated otherwise, all material is copyright © The University of Edinburgh 2019. Course specific materials are created by University of Edinburgh staff for you to use in your studies. You should not share, publish or sell these outside the University