275 search results for "anova"

European MEP Data, Part 2

May 11, 2014
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European MEP Data, Part 2

Following last week's short examination, I now wanted to drill down a bit more in the voting behaviour as given in data from votewatch.eu on voting of MEPs.Votewatch's Data describe how often MEPs voted what in the European Parliament. For each MEP the number of votes, percentages Yes, No, Abstain, number of elections and...

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Modelling seasonal data with GAMs

May 9, 2014
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Modelling seasonal data with GAMs

In previous posts I have looked at how generalized additive models (GAMs) can be used to model non-linear trends in time series data. At the time a number of readers commented that they were interested in modelling data that had more than just a trend component; how do you model data collected throughout the year over many years with...

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Introducing Statwing

April 27, 2014
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Introducing Statwing

Recently, Greg Laughlin, the founder of a new statistical software called Statwing, let me try his product for free. I happen to like free things very much (the college student is strong within me) so I gave it a try. I mostly like how easy it is to use: For instance, to relate two attributes

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Simpson’s Paradox Is Back

April 21, 2014
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Simpson’s Paradox Is Back

The latest issue of the American Statistician has a set of thought-provoking point/counterpoint papers on Simpson’s Paradox, with a tie-in to the controversial issue of causality. (I will not address the causality issue here.) Since I have long had my own thoughts about Simpson’s, I’ll postpone the topic I had planned to post this week,

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Simpson’s Paradox Is Back

April 21, 2014
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Simpson’s Paradox Is Back

The latest issue of the American Statistician has a set of thought-provoking point/counterpoint papers on Simpson’s Paradox, with a tie-in to the controversial issue of causality. (I will not address the causality issue here.) Since I have long had my own thoughts about Simpson’s, I’ll postpone the topic I had planned to post this week,

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Interpreting interaction coefficient in R (Part1 lm)

April 8, 2014
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Interpreting interaction coefficient in R (Part1 lm)

Interaction are the funny interesting part of ecology, the most fun during data analysis is when you try to understand and to derive explanations from the estimated coefficients of your model. However you do need to know what is behind these estimate, there is a mathematical foundation between them that you need to be aware

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Scraping organism metadata for Treebase repositories from GOLD using Python and R

Scraping organism metadata for Treebase repositories from GOLD using Python and R I recently wanted to get hold of habitat/phenotype/sequencing metadata for the individual organisms of an archived Treebase project.) The GOLD database holds more than 18000 full genomes. For many of these it provides pretty good metadata (GOLDcards) which are indirectly linked to...

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R User Group Activity for Q1 2014

March 27, 2014
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R User Group Activity for Q1 2014

by Joseph Rickert Worldwide R user group activity for the first Quarter of 2014 appears to be way up compared to previous years as the following plot shows. The plot was built by counting the meetings on Revolution Analytics R Community Calendar. R users continue to value the live, in person events and face-to-face meetings with their peers. Moreover,...

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Seasonal Unit Roots

March 26, 2014
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Seasonal Unit Roots

As discussed in the MAT8181 course, there are – at least – two kinds of non-stationary time series: those with a trend, and those with a unit-root (they will be called integrated). Unit root tests cannot be used to assess whether a time series is stationary, or not. They can only detect integrated time series. And the same holds...

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Normality and Testing for Normality

March 21, 2014
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Normality and Testing for Normality

How do we test for normality, and are normality tests really sensitive in the tails?

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