clehene : statistics   117

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research  statistics  datasets  reference
5 weeks ago by clehene
stripe/rainier: Bayesian inference in Scala.
Bayesian inference in Scala. Contribute to stripe/rainier development by creating an account on GitHub.
bayesian  scala  statistics  bayesian-inference  jvm  markov
7 weeks ago by clehene
Prophet | Prophet is a forecasting procedure implemented in R and Python. It is fast and provides completely automated forecasts that can be tuned by hand by data scientists and analysts.
Prophet is a forecasting procedure implemented in R and Python. It is fast and provides completely automated forecasts that can be tuned by hand by data scientists and analysts.
analytics  forecasting  python  facebook  seasonality  statistics
11 weeks ago by clehene
CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers: aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;) - CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
probabilistic-programming  bayesian  statistics  python  probability  bayes  book
12 weeks ago by clehene
The Central Limit Theorem and its misuse
The central limit theorem is possibly the most famous theorem in all of statistics, being widely used in any field that wants to infer something or make predictions from gathered data. A first (simple) version of it was introduced in the eighteenth century, first by de Moivre and then later in a more refined way by Laplace, but it wasn't until around 1935 that the theorem as we know it today was published. The goal of these notes is to explain in broad terms what it says and, more im...
statistics  clt
december 2019 by clehene
Studies of scientific bias targeting the right problems | News Center | Stanford Medicine
The biggest single source of bias across all fields of science comes from so-called small-study effects, Stanford researchers report.
bias  reasearch  metastudy  statistics
march 2019 by clehene
eclesh/welford: welford implements a one-pass algorithm for computing mean and variance
welford implements a one-pass algorithm for computing mean and variance - eclesh/welford
welford  statistics  variance
january 2019 by clehene
Accurately computing sample variance online
How to compute sample variance (standard deviation) as samples arrive sequentially, avoiding numerical problems that could degrade accuracy.
running  variance  statistics  algorithms
january 2019 by clehene
Actuarial Outpost
Actuarial discussion forum and jobs, home of the Actuarial Outpost
actuarial  risk  insurance  statistics
april 2018 by clehene
Using T-tests to benchmark page load performance – GoToAssist Product Blog – Medium
Loading dashboard page of GotoAssist Service desk. - Gist is a simple way to share snippets of text and code with others.
statistics  performance
january 2018 by clehene
Probabilistic programming: an annotated bibliography
Earlier this year we launched a research report on probabilistic programming, an emerging programming paradigm that makes it easier to describe and train pro...
probability  statistics
october 2017 by clehene
Data Analysis for… by Rafael A Irizarry et al. [PDF/iPad/Kindle]
Data analysis is now part of practically every research project in the life sciences. In this book we use data and computer code to teach the necessary statistical concepts and programming skills to become a data analyst. Instead of showing theory first and then applying it to toy examples, we start with actual applications and describe the theo...
data-science  statistics  book
august 2017 by clehene
cavaunpeu/statistical-rethinking: Solutions for the practice problems
statistical-rethinking - Solutions for the practice problems
statistics  bayesian
july 2017 by clehene
Why isn't everything normally distributed?
Heights are normally distributed because height is determined by many factors. But why are other things with many inputs not normally distributed?
statistics  distribution
july 2017 by clehene
Top 20 Facebook Statistics - Updated May 2017
Facebook represents a huge potential market for your social media efforts, but it is becoming increasingly difficult to stand out from the crowd. The following statistics highlight some relevant Facebook facts and can ultimately help you to navigate it better, increasing your return on investment (ROI) and leading to greater marketing success.
facebook  statistics
june 2017 by clehene
tdunning/t-digest: A new data structure for accurate on-line accumulation of rank-based statistics such as quantiles and trimmed means
t-digest - A new data structure for accurate on-line accumulation of rank-based statistics such as quantiles and trimmed means
algorithm  statistics  aggregation  streaming  algorithms  analytics
june 2017 by clehene
Four characterizations of the normal distribution
Four different properties of the normal (Gaussian) probability distribution that uniquely define it.
statistics  normal  distribution
june 2017 by clehene
Why we should love null results – The 100% CI
But what happens when p ≥ .05? P-hacking aside: When was the last time you read a paper saying “turns out we were wrong, p > .05″? NHST only tests H0. The p-value says nothing about the probability of Hshinynew being true
statistics  nhst  methodology
june 2017 by clehene
Paradoxes of probability and other statistical strangeness
Sometimes statistics and probability can produce unexpected or counter-intuitive results. If we're hoping to use numbers to make good decisions, we should be wary of the traps.
statistics  fallacy  paradox  simson  berkson
april 2017 by clehene
The Probability and Statistics Cookbook
A succinct reference in probability theory and statistics
probability  statistics  cheatsheet
november 2016 by clehene
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