380 search results for "boxplot"

Win Your Snake Draft: Calculating “Value Over Replacement” using R

April 14, 2013
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Win Your Snake Draft: Calculating “Value Over Replacement” using R

In prior posts, I have demonstrated how to download, calculate, and compare fantasy football projections from ESPN, CBS, and NFL.com and how to calculate players’ risk levels. In this post, I will demonstrate how to win your snake The post Win Your Snake Draft: Calculating "Value Over Replacement" using R appeared first on Fantasy Football Analytics.

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Global Distribution of Breast Cancer: some initial considerations

April 10, 2013
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Global Distribution of Breast Cancer: some initial considerations

As mentioned on a previous post, I am interested in analysing if people’s ‘unhealthy’ lifestyle is associated to new cases of cancer diagnosed globally. The outcome variable I want to explore (at least for now), is the number of new cases of breast cancer in 100,000 female residents. I have this data for 173...

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Mobile version of the graph gallery

April 10, 2013
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Mobile version of the graph gallery

The R Graph Gallery has been a popular website for many years now. The number of graphics keeps growing as people send me their code. When browsing the website with a mobile device the experience was frustrating, as too much … Continue reading →

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Organise your data

April 5, 2013
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Use R to specify factors, recode variables and begin by-group analyses. Video Files This file contains data on pain score after laparoscopic vs. open hernia repair. Age, gender and primary/recurrent hernia also included. The ultimate aim here is to work out which of these factors are associated with more pain after this operation. lap_hernia Script

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A pictorial history of US large cap correlation

April 1, 2013
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A pictorial history of US large cap correlation

How has the distribution of correlations changed over the last several years? Previously Posts about correlation boxplots explained Data Daily returns of 443 large cap US stocks from 2004 through 2012 were used.  The sample correlations — almost 98,000 of them — during each year were created. If we were actually using the correlations, then … Continue reading...

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Data visualization with R and ggplot2

March 28, 2013
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Data visualization with R and ggplot2

I’m working on a one-hour ggplot2 lecture for the San Diego R users group, which I will post here when I’m done. I think there are many great intro to R data visualization resources out there so I’ll only share working examples on my blog. A retail chain client employs a few hundred field agents who perform

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Generalized Pairs Plot: It’s about time!

March 28, 2013
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Generalized Pairs Plot: It’s about time!

JW Emerson, WA Green, B Schloerke, J Crowley, D Cook, H Hofmann, H Wickham (2013) The Generalized Pairs Plot. Journal of Computational and Graphical Statistics 22(1). Here's a free preprint version. Until this new paper and implementation by Emerson et al., there were no widely available pairs plots that accommodated both numerical and categorical fields.

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Benford law and lognormal distributions

March 28, 2013
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Benford law and lognormal distributions

Benford’s law is nowadays extremely popular (see e.g. http://en.wikipedia.org/…). It is usually claimed that, for a given set data set, changing units does not affect the distribution of the first digit. Thus, it should be related to scale invariant distributions. Heuristically, scale (or unit) invariance means that the density of the measure  (or probability function) should be proportional to...

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Explore March Madness face-offs with this NCAA data visualizer

March 22, 2013
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Explore March Madness face-offs with this NCAA data visualizer

If you're laying down a friendly bet on the March Madness games or just tweaking your fantasy roster, this NCAA Data Visualizer by Rodrigo Zamith will be a boon. Just choose two teams to compare head-to-head, choose an attribute to compare them on. You can look at more than a dozen invividual player attributes (e.g. points scored, assists, 3-point...

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Extracting Information From Objects Using Names()

March 17, 2013
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Extracting Information From Objects Using Names()

One of the big differences between a language like Stata compared to R is the ability in R to handle many different types of objects at once, and combine them together or pull them apart.  I had a post about objects last year, but I thought I'd sh...

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