1627 search results for "Excel"

Throw some, throw some STATS on that map…(Part 1)

July 12, 2013
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Throw some, throw some STATS on that map…(Part 1)

R is a very powerful and free (and fun) software package that allows you to do, pretty much anything you could ever want. Someone told me that there’s even code that allows you to order pizza (spoiler alert: you actually cannot order pizza using R :( ). But if you’re not hungry, the statistical capabilities

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A Julia Meta Tutorial

July 11, 2013
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A Julia Meta Tutorial

If you are thinking about taking Julia, the hot new mathematical, statistical, and data-oriented programming language, for a test drive, you might need a little bit of help. In this blog we round up some great posts discussing various aspects … Continue reading → The post A Julia Meta Tutorial appeared first on Data Community DC.

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UseR! 2013 – Day 1 notes

July 10, 2013
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UseR! 2013 – Day 1 notes

Hadley Wickham presents at the useR! 2013 conference, July 10 2013 Today marked the first day of the 2103 useR! conference, a gathering of more than 350 R users from around the world. The conference has been quite a success so far, kicking off yesterday with a day of tutorials followed by a tapas-fueled welcome party in the center...

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Parallel Random Number Generation using TRNG

July 10, 2013
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Parallel Random Number Generation using TRNG

To my surprise and disappointment, popular scientific libraries like Boost or GSL provide no native support for parallel random number generation. Recently I came across TRNG, an excellent random number generation library for C++ built specifically with parallel architectures in mind. Over the last few days I’ve been trawling internet forums and reading discussions about The post Parallel...

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user2013: The caret tutorial

July 9, 2013
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user2013: The caret tutorial

This afternoon I went to Max Kuhn’s tutorial on his caret package. caret stands for classification and regression (something beginning with e) trees. It provides a consistent interface to nearly 150 different models in R, in much the same way as the plyr package provides a consistent interface to the apply functions. The basic usage

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Another view of ordinary regression

July 8, 2013
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Another view of ordinary regression

This is something I’ve been meaning to write for ages. My formal training for most things is limited. Like a lot of folks, I’m an autodidact. This is good in that I’m always learning and always studying those things that I enjoy. At the same time, it means that I take in information in a

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Interactive Heatmaps (and Dendrograms) – A Shiny App

July 7, 2013
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Interactive Heatmaps (and Dendrograms) – A Shiny App

Heatmaps are a great way to visualize data matrices. Heatmap color and organization can be used to  encode information about the data and metadata to help learn about the data at hand. An example of this could be looking at the raw data  or hierarchically clustering samples and variables based on their similarity or differences.

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RFM Customer Analysis with R Language

July 7, 2013
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RFM Customer Analysis with R Language

For database marketing or direct marketing people, they are always concerned about two questions before they send out mails or make calls to their customers:- How can they segment the customers in the database to find out who are more likely to response to their mails or buy their products? Which type of customers they

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Which airline should you be loyal to?

July 2, 2013
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Which airline should you be loyal to?

LOYALTY PROGRAM CHOICE BASED ON DEPARTURE COUNT If you read Decision Science News, you’re probably a professor or grad student or researcher or policy type who flies around a lot to conferences, symposia, workshops, tutorials, summer schools, and all-hands meetings. You travel the globe to give talks and work with co-authors. All this flying around The post Which...

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Some Common Approaches for Analyzing Likert Scales and Other Categorical Data

July 1, 2013
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Some Common Approaches for Analyzing Likert Scales and Other Categorical Data

Analyzing Likert scale responses really comes down to what you want to accomplish (e.g. Are you trying to provide a formal report with probabilities or are you trying to simply understand the data better). Sometimes a couple of graphs are sufficient and a formalize statistical test isn’t even necessary. However, with how easy it is

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