319 search results for "boxplot"

Analyze web traffic data with Google Analytics and R

February 7, 2013
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Analyze web traffic data with Google Analytics and R

If you run an e-commerce site, blog or other web property there's a good chance you use Google Analytics to monitor traffic, look at visitor sources, and measure conversions. And while Google Analytics is quite powerful at looking at historic activity on your site, it lacks much in the way of predictive analytics. That's where R shines of course,...

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"I don’t wanna grow up": Age / value relationships for football players

February 1, 2013
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"I don’t wanna grow up": Age / value relationships for football players

Let's get back to the age-value relationship from my last post. I did some more plotting to see on which position this inversed U-shaped relationship is strongest. Please note, that I use a dataframe called eu.players throughout this post, which holds downloaded football player information from transfermarkt.de.But first, let us get back to the original graph.

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A slightly different introduction to R, part II

January 27, 2013
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A slightly different introduction to R, part II

In part I, we looked at importing data into R and simple ways to manipulate data frames. Once we’ve gotten our data safely into R, the first thing we want to do is probably to make some plots. Below, we’ll make some simple plots of the made-up comb gnome data. If you want to play

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(not provided): Using R and the Google Analytics API

January 11, 2013
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(not provided): Using R and the Google Analytics API

For power users of Google Analytics, there is a heavy dose of spreadsheet work that accompanies any decent analysis.  But even with Excel in tow, it’s often difficult to get the data just right without resorting to formula hacks and manual table formatting.  This is where the Google Analytics API and R can come very (not provided): Using...

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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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