3612 search results for "gis"

What Would Cohen Have Titled “The Earth is Round (p < .05)” in 2014?

June 25, 2014
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What Would Cohen Have Titled “The Earth is Round (p < .05)” in 2014?

The area of bibliometrics is not my area of expertise but is still of interest as a researcher. I sometimes think about how Google has impacted the way we title articles. Gone are the days of witty, snappy titles. Title … Continue reading →

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Do you believe in World Cup superstition?

June 24, 2014
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Do you believe in World Cup superstition?

If you believe in supernatural causality, you will love what the numbers of the World Cup have to say which team is going to win this Cup in Brazil. According to this numerology approach neither Brazil nor Germany or Netherlands will be the winner, but Uruguay. The table below shows my reason. This was produced

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Statistics and R at the Intel ISEF Science Fair

June 24, 2014
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Statistics and R at the Intel ISEF Science Fair

by Wayne Smith, Ph.D. California State University, Northridge Editor's note: This post was abstracted from the monthly newsletter of the Southern California Chapter of the ASA. On May 13th and 14th, the Intel International Science and Engineering Fair (Intel ISEF) the world’s largest international pre-college competition, was held at the Los Angeles Convention Center. I was blessed with the...

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Using Julia As A ‘Glue’ Language

June 24, 2014
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While much of the focus in the Julia community has been on the performance aspects of Julia relative to other scientific computing languages, Julia is also perfectly suited to ‘glue’ together multiple data sources/languages. In this blog post, I will cover how to create an interactive plot using Gadfly.jl, by first preparing the data using Related posts:

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Bank of America uses R for reporting

June 23, 2014
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A recent FastCoLabs article, "The 9 Best Languages For Crunching Data", starts its list with the R language: It would be downright negligent to start this list with any language other than R. It has been kicking around since 1997 as a free alternative to pricey statistical software, such as Matlab or SAS. But over the past few years,...

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Coloring the world – Extracting user specific color palettes from Tableau Workbooks

June 22, 2014
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Coloring the world – Extracting user specific color palettes from Tableau Workbooks

If you read some of my last blog post you may notice that R got a new companion called Tableau. Tableau is an easy to use and mighty BI toolbox for visualizing all kinds of data and I suggest everybody to give it a trial. One of the things that I like very much is that it gives...

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Multilevel modeling of community composition with imperfect detection

June 19, 2014
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Multilevel modeling of community composition with imperfect detection

This is a guest post generously provided by Joe Mihaljevic. A common goal of community ecology is to understand how and why species composition shifts across space. Common techniques to determine which environmental covariates might lead to such shifts typically rely on ordination of community data to reduce the amount of data. These techniques include redundancy analysis (RDA), canonical...

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Upcoming R Training Course in Boston

June 18, 2014
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Upcoming R Training Course in Boston

R for Software Developers and Data Analysts Saturday June 28, 2014 9:00am-4:00pm Microsoft NERD, Cambridge, MA I’ll be presenting a one day professional development workshop on R programming for software developers and data scientists, sponsored by the Greater Boston Chapter of … Continue reading →

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The RoughSets R Package (free webinar)

June 18, 2014
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The RoughSets R Package (free webinar)

Ray DiGiacomo, President of The Orange County R User Group (OC-RUG) in Southern California, contacted us to spread the word about the free webinar they will host on the new “RoughSets” package. RoughSets package This free webinar will provide an introduction to the “RoughSets” package, which provides comprehensive implementations of rough set theory (RST) and

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PITFALL: Did you really mean to use matrix(nrow, ncol)?

June 17, 2014
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PITFALL: Did you really mean to use matrix(nrow, ncol)?

Are you a good R citizen and preallocates your matrices? If you are allocating a numeric matrix in one of the following two ways, then you are doing it the wrong way!x <- matrix(nrow=500, ncol=100)orx <- matrix(NA, nrow=500, ncol=100)Why? Becau...

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