335 search results for "boxplot"

Why Do the New Orleans Saints Lose? Data Visualization II

December 26, 2012
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Why Do the New Orleans Saints Lose? Data Visualization II

I’m going to continue with my ‘making data visually appealing to the masses’ kick. I happen to like graphics and graphing data. I also happen to like American football (For the record, however, I’m a soccer player first, a rugby … Continue reading →

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Miles of iles

December 24, 2012
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Miles of iles

An explanation of quartiles, quintiles deciles, and boxplots. Previously “Again with variability of long-short decile tests” and its predecessor discusses using deciles but doesn’t say what they are. The *iles These are concepts that have to do with approximately equally sized groups created from sorted data. There are 4 groups with quartiles, 5 with quintiles … Continue reading...

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Generation of E-Learning Exams in R for Moodle, OLAT, etc.

December 20, 2012
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Generation of E-Learning Exams in R for Moodle, OLAT, etc.

(Guest post by Achim Zeileis) Development of the R package exams for automatic generation of (statistical) exams in R started in 2006 and version 1 was published in JSS by Gr?n and Zeileis (2009). It was based on standalone Sweave exercises, that can be combined …Read more »

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NHS Winter Situation Reports: Shiny Viewer v2

December 18, 2012
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NHS Winter Situation Reports: Shiny Viewer v2

Having got my NHS Winter sitrep data scraper into shape (I think!), and dabbled with a quick Shiny demo using the R/Shiny library, I thought I’d tidy it up a little over the weekend and long the way learn a few new presentation tricks. To quickly recap the data availability, the NHS publish a weekly

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Making Data Visually Appealing

December 16, 2012
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Making Data Visually Appealing

I’ve recently been considering the graphical presentation of data. I get the feeling that we, ecologists/scientsits, could be better at data presentation. Graphs must be informative, but they don’t have to be ugly. I think that making visually appealing charts … Continue reading →

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Data Science, Data Analysis, R and Python

The October 2012 issue of Harvard Business Review prominently features the words “Getting Control of Big Data” on the cover, and the magazine includes these three related articles:“Big Data: The Management Revolution,” by Andrew McAfee and Erik Brynjolfsson, pages 61 – 68;“Data Scientist: The Sexiest Job of the 21st Century,” by Thomas H. Davenport and D.J. Patil, pages...

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We NEED more data

November 22, 2012
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We NEED more data

Email One of the historic difficulties of doing research on urban energy systems has been the limited availability of data at sufficiently detailed spatial resolutions. Without this data, you might end up relying on aggregate information about the built environment, building occupants, and local geography that doesn't apply to the specifics of a particular neighbourhood

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Data types, part 3: Factors!

November 21, 2012
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Data types, part 3: Factors!

In this third part of the data types series, I'll go an important class that I skipped over so far: factors.Factors are categorical variables that are super useful in summary statistics, plots, and regressions. They basically act like dummy variables t...

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The Hour of Hell of Every Morning – Commute Analysis, April to October 2012

November 19, 2012
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The Hour of Hell of Every Morning – Commute Analysis, April to October 2012

IntroductionSo a little while ago I quit my job.Well, actually, that sounds really negative. I'm told that when you are discussing large changes in your life, like finding a new career, relationship, or brand of diet soda, it's important to frame things positively.So let me rephrase that - I've left job I previously held to pursue other directions. Why?...

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Textual Healing Part II

November 15, 2012
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Textual Healing Part II

Yesterday’s post showed a number of quick coding options for changing text in a basic ggplot. Here’s another two tricks for fine-tuning faceted plots. Again, let’s load our made up data about tooth growth (a real dataset in R, ToothGr...

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