# statistics

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## So You Think You Have a Power Law — Well Isn&#039;t That Special

So You Think You Have a Power Law — Well Isn't That Special?
So you’ve got your AdWords test all set up: Will people go for the headline “Code Review Tools” or “Tools for Code Review?” Gee they’re both so exciting!

## Nassim Nicholas Taleb Home and Professiona

Abstract We introduce a new variable selection technique called the Permuted Inclusion Criterion (PIC) based on augmenting the predictor space X with a row-permuted version denoted Xpi. We adopt the linear regression setup with n observations on p variables.

## ScholarlyCommons - Shaun Lysen: Permuted Inclusion Criterion: A

By CARI TUNA Is the current economic slump worse than the recession of the early 1980s? Measured by unemployment, the answer appears to be no, or at least not yet. The jobless rate was 10.2% in October, compared with a peak of 10.8% in November and December of 1982. But viewed another way, the current recession looks worse, not better.

## Wikimania2007-SethAnthony.pdf

I’ll copy and paste my notes for some of the talks at Wikimania 2007 here, in case it’s helpful so that everyone can follow what’s going on. As such they will be in point / summary form, rather than well-formed prose: Talk:”Where have all the editors gone?”

## http://norvig.com/experiment-design.html

When an experimental study states "The group with treatment X had significantly less disease ( p = 1%)", many people interpret this statement as being equivalent to "there is a 99% chance that if I do treatment X it will prevent disease."
Estimating by Minimizing \newcommand{\Expect}[1]{\mathbb{E}\left[ #1 \right]} \newcommand{\Var}[1]{\mathrm{Var}\left[ #1 \right]} \newcommand{\Expectwrt}[2]{\mathbb{E}_{#2}\left[ #1 \right]} \newcommand{\Varwrt}[2]{\mathrm{Var}_{#2}\left[ #1 \right]} \DeclareMathOperator*{\argmin}{argmin}

## WikiXRay

The main goal of this project is to develop a robust and extensible software tool for an in-depth quantitative analysis of the whole Wikipedia project.

## Mediation (David A. Kenny)

David A. Kenny April 3, 2012 Recently updated. Please let me know if your find any errors or have any suggestions.
December 31, 2006 | Tags: digg , diggstatus , statistics , data , analysis The Experiment Saturday, December 9th, I decided to run an experiment.

## Margin of Error and Confidence Levels Made Simple

Pamela Hunter February 26, 2010 A survey is a valuable assessment tool in which a sample is selected and information from the sample can then be generalized to a larger population. Surveying has been likened to taste-testing soup – a few spoonfuls tell what the whole pot tastes like. The key to the validity of any survey is randomness.
Subjective judgments, an essential information source for science and policy, are problematic because there are no public criteria for assessing judgmental truthfulness. I present a scoring method for eliciting truthful subjective data in situations where objective truth is unknowable. The method assigns high scores not to the most common answers but to the answers that are more common than collectively predicted, with predictions drawn from the same population.

## The Statistics Homepage

"As a professional medical statistician of some 40 years standing, I can unreservedly recommend this textbook as a resource for self-education, teaching and on-the-fly illustration of specific statistical methodology in one-to-one statistical consulting.

## Introduction to the Scientific Method

Introduction to the Scientific Method The scientific method is the process by which scientists, collectively and over time, endeavor to construct an accurate (that is, reliable, consistent and non-arbitrary) representation of the world. Recognizing that personal and cultural beliefs influence both our perceptions and our interpretations of natural phenomena, we aim through the use of standard procedures and criteria to minimize those influences when developing a theory.

## Correlation

In the following topics, we will first review techniques used to identify patterns in time series data (such as smoothing and curve fitting techniques and autocorrelations), then we will introduce a general class of models that can be used to represent time series data and generate predictions (autoregressive and moving average models). Finally, we will review some simple but commonly used modeling and forecasting techniques based on linear regression. For more information see the topics below. General Introduction In the following topics, we will review techniques that are useful for analyzing time series data, that is, sequences of measurements that follow non-random orders. Unlike the analyses of random samples of observations that are discussed in the context of most other statistics, the analysis of time series is based on the assumption that successive values in the data file represent consecutive measurements taken at equally spaced time intervals.