# 1802 search results for "tutorial"

## R version of “An exploratory technique for visualizing the distributions of 100 variables:”

September 10, 2014
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Rick Wicklin (@RickWicklin) made a recent post to the SAS blog on An exploratory technique for visualizing the distributions of 100 variables. It’s a very succinct tutorial on both the power of boxplots and how to make them in SAS (of course). I’m not one to let R be “out-boxed”, so I threw together a

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## Build a SPAM filter with R

September 8, 2014
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You can find the complete code on github: https://github.com/JulianHill/R-Tutorials/blob/master/spam_class_r.r   Introduction: The topic Machine Learning gets more and more important. The number of data sources grows everyday and it makes it hard to get... The post Build a SPAM filter with R appeared first on ThinkToStart.

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## Long Memory and the Nile: Herodotus, Hurst and H

September 4, 2014
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by Joseph Rickert The ancient Egyptians were a people with long memories. The lists of their pharaohs went back thousands of years, and we still have the names and tax assessments for certain persons and institutions from the time of Ramesses II. When Herodotus began writing about Egypt and the Nile (~ 450 BC), the Egyptians who knew that...

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## Baseball: Probability of winning conditional on runs, hits, walks and errors

September 2, 2014
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If a team scores X runs, what's the probability it will win the game? The post Baseball: Probability of winning conditional on runs, hits, walks and errors appeared first on Decision Science News.

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## Yet another R package primer

August 28, 2014
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Hadley Wickham is writing what will surely be a great book about the basics of R packages. And Hilary Parker wrote a very influential post on how to write an R package. So it seems like that topic is well covered. Nevertheless, I’d been thinking for some time that I should write another minimal tutorial

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## TTTAR2: My First Shiny App with Bootstrap – #RUGSMAPS

August 26, 2014
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Thing To Try After useR! part 2 (TTTAR2) Originally, this post was supposed to be a sequel to TTTAR1 about h2o machine learning. Since TTTAR1 I have been carrying out more h2o tests both locally and on the cloud with the very kind support of Nick Elprin from Domino. The more...

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## Making Your Code Citable

August 26, 2014
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Original post from GitHub Guides:Digital Object Identifiers (DOI) are the backbone of the academic reference and metrics system. If you’re a researcher writing software, this guide will show you how to make the work you share on GitHub citable by archiving one of your GitHub repositories and assigning a DOI with the data...

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## The Chi-Squared Test of Independence – An Example in Both R and SAS

$The Chi-Squared Test of Independence – An Example in Both R and SAS$

Introduction The chi-squared test of independence is one of the most basic and common hypothesis tests in the statistical analysis of categorical data.  Given 2 categorical random variables, and , the chi-squared test of independence determines whether or not there exists a statistical dependence between them.  Formally, it is a hypothesis test with the following null and

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## Continuous or Discrete Latent Structure? Correspondence Analysis vs. Nonnegative Matrix Factorization

August 25, 2014
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A map gives us the big picture, which is why mapping has become so important in marketing research. What is the perceptual structure underlying the European automotive market? All we need is a contingency table with cars as the rows, attributes as the ...

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## Do your "data janitor work" like a boss with dplyr

August 20, 2014
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Data “janitor-work” The New York Times recently ran a piece on wrangling and cleaning data: “For Big-Data Scientists, ‘Janitor Work’ Is Key Hurdle to Insights” Whether you call it “janitor-work,” wrangling/munging, cleaning/cleansing/scrubbing, tidying, or something else, the article above is worth a read (even though it implicitly denigrates the important work that your housekeeping staff does). It’s...

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