2068 search results for "regression"

Mastering Matrices

April 7, 2013
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Mastering Matrices

R has many ways to store information.  Most of the time, our data comes in the form of a dataset, which we bring into R as a data.frame object. However, there are times when we want to use matrices as well. This post will show you how matrices can...

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Worry about correctness and repeatability, not p-values

April 5, 2013
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Worry about correctness and repeatability, not p-values

In data science work you often run into cryptic sentences like the following: Age adjusted death rates per 10,000 person years across incremental thirds of muscular strength were 38.9, 25.9, and 26.6 for all causes; 12.1, 7.6, and 6.6 for cardiovascular disease; and 6.1, 4.9, and 4.2 for cancer (all P < 0.01 for linear Related posts:

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An Introduction to SAS for R Programmers

April 4, 2013
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by Joseph Rickert Life decisions are usually much too complicated to be attributed to any single cause, but one important reason that I am here at Revolution today is that I ignored suggestions from well-meaning faculty back in graduate school to work more in SAS rather than doing everything in R. There was a heavy emphasis on SAS then:...

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a brief on naked statistics

April 2, 2013
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a brief on naked statistics

Over the last Sunday breakfast I went through Naked Statistics: Stripping the Dread from the Data. The first two pages managed to put me in a prejudiced mood for the rest of the book. To wit: the author starts with some math bashing (like, no one ever bothers to tell us about the uses of

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What’s New in Release 6.2: Additional ScaleR Features

April 2, 2013
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by Thomas Dinsmore Revolution R Enterprise Release 6.2 is in track for General Availability on April 22. In previous posts, I've commented on support for open source R 2.15.3 and Stepwise Regression. Today I'll wrap this series with a summary of some of the other new features supported in this release. Parallel Random Number Generation For analysts seeking to...

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Introducing the healthvis R package – one line D3 graphics with R

April 2, 2013
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We have been a little slow on the posting for the last couple of months here at Simply Stats. That’s bad news for the blog, but good news for our research programs! Today I’m announcing the new healthvis R package … Continue reading →

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p-values are (possibly biased) estimates of the probability that the null hypothesis is true

March 31, 2013
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p-values are (possibly biased) estimates of the probability that the null hypothesis is true

Last week, I posted about statisticians’ constant battle against the belief that the p-value associated (for example) with a regression coefficient is equal to the probability that the null hypothesis is true, for a null hypothesis that beta is zero or negative. I argued that (despite our long pedagogical practice) there are, in fact, many

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How do Dew and Fog Form? Nature at Work with Temperature, Vapour Pressure, and Partial Pressure

How do Dew and Fog Form?  Nature at Work with Temperature, Vapour Pressure, and Partial Pressure

In the early morning, especially here in Canada, I often see dew – water droplets formed by the condensation of water vapour on outside surfaces, like windows, car roofs, and leaves of trees.  I also sometimes see fog – water droplets or ice crystals that are suspended in air and often blocking visibility at great

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More ordinal data display

March 30, 2013
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More ordinal data display

The past two weeks I made a post regarding analyzing ordinal data with R and JAGS. The calculations in the second part made me realize I could actually get top two box intervals out of R. This demonstrated here. For that I needed the inv...

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Lots of data != "Big Data"

March 28, 2013
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Lots of data != "Big Data"

by Joseph Rickert When talking with data scientists and analysts — who are working with large scale data analytics platforms such as Hadoop — about the best way to do some sophisticated modeling task it is not uncommon for someone to say, "We have all of the data. Why not just use it all?" This sort of comment often...

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