Monthly Archives: November 2016

On the German Tank / Taxicab Problem

November 30, 2016
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On the German Tank / Taxicab Problem

I always get giddy when I can apply real statistics and math to problems in my life. Recently, I had an opportunity to apply the ‘Taxicab Problem’ to something that came up at work. Given that I work for a ridesharing platform and I was quite literally counting “taxis” (or at least cars meant to drive others around), this...

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The hourly heatmap with ggplot2

November 30, 2016
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The hourly heatmap with ggplot2

a quick follow up to my last post - I’ve had a few folk get in touch following my last post, all commenting on the last plot : Most of these enquiries went along the following lines: “I hadn’t thought of doing that. It looks really ...

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asymptotically exact inference in likelihood-free models [a reply from the authors]

November 30, 2016
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asymptotically exact inference in likelihood-free models [a reply from the authors]

Thanks for the comments on the paper! A few additional replies to augment what Amos wrote: This however sounds somewhat intense in that

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Euler Problem 1: Multiples of 3 or 5

November 30, 2016
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Euler Problem 1: Multiples of 3 or 5

Solutions to Euler Problem 1 in the R language for statistical computing. This problem asks to find the sum of the multiples of 3 or 5 below 1000. Continue reading → The post Euler Problem 1: Multiples of 3 or 5 appeared first on The Devil is in the Data.

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Frequency and chi-square test for independence Exercises

November 30, 2016
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Frequency and chi-square test for independence Exercises

In this exercise, we cover some basics on frequency tables. We also briefly look at chi-square test for independence to find relationships of two variables. Before proceeding, it might be helpful to look over the help pages for the table, summary, and margin.table functions. Answers to the exercises are available here. If you obtained a

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Missing Values, Data Science and R

November 30, 2016
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Missing Values, Data Science and R

by Joseph Rickert One great advantages of working in R is the quantity and sophistication of the statistical functions and techniques available. For example, R’s quantile() function allows you to select one of the nine different methods for computing quantiles. Who would have thought there could be so many ways to do something that seems

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Jupyter And R Markdown: Notebooks With R

November 30, 2016
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Jupyter And R Markdown: Notebooks With R

When working on data science problems, you might want to set up an interactive environment to work and share your code for a project with others. You can easily set this up with a notebook.  In other cases, you’ll just want to communicate about t...

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Microsoft R Open 3.3.2 now available

November 30, 2016
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Microsoft R Open 3.3.2, Microsoft's enhanced distribution of open source R, is now available for download for Windows, Mac, and Linux. This update upgrades the R language engine to version 3.3.2, adds new bundled packages and updates others, and upgrades the Intel Math Kernel Libraries. The updated R 3.3.2 engine includes some performance improvements (particularly in calculation of eigenvalues),...

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How to Summarize a Data Frame by Groups in R

November 30, 2016
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How to Summarize a Data Frame by Groups in R

Sometimes, when you’re analyzing a data set and you want to get a complete picture of it, you want calculate the metrics on all the observations for each variable. Let’s say, for example, that you run a small zoo and want to inventory the cost of all your animals. To calculate this in a spreadsheet,

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satRday in Cape Town (from Exegetic Analytics)

November 30, 2016
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satRday in Cape Town (from Exegetic Analytics)

The second satRday (and first satRday on African soil) will happen in Cape Town on 18 August 2017. It’s going to be a one day celebration of R. We have a trio of phenomenal keynote speakers (Hilary Parker, Jenny Bryan and Julia Silge) who will be giving inspiring talks at the conference and also conducting … The post

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