Blog Archives

Example 7.28: Bubble plots

March 22, 2010
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Example 7.28: Bubble plots

A bubble plot is a means of displaying 3 variables in a scatterplot. The z dimension is presented in the size of the plot symbol, typically a circle. The area or radius of the circle plotted is proportional to the value of the third variable. This c...

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Example 7.27: probability question reconsidered

March 15, 2010
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Example 7.27: probability question reconsidered

In Example 7.26, we considered a problem, from the xkcd blog:Suppose I choose two (different) real numbers, by any process I choose. Then I select one at random (p= .5) to show Nick. Nick must guess whether the other is smaller or larger. Being righ...

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Example 7.26: probability question

March 8, 2010
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Example 7.26: probability question

Here's a surprising problem, from the xkcd blog.Suppose I choose two (different) real numbers, by any process I choose. Then I select one at random (p= .5) to show Nick. Nick must guess whether the other is smaller or larger. Being right 50% of the ...

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Example 7.25: compare draws with distribution

March 5, 2010
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Example 7.25: compare draws with distribution

In example 7.24, we demonstrated a Metropolis-Hastings algorithm for generating observations from awkward distributions. In such settings it is desirable to assess the quality of draws by comparing them with the target distribution.Recall that the dis...

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Example 7.23: the Monty Hall problem

January 20, 2010
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Example 7.23: the Monty Hall problem

The Monty Hall problem illustrates a simple setting where intuition often leads to a solution different from formal reasoning. The situation is based on the game show Let's Make a Deal. First, Monty puts a prize behind one of three doors. Then the player chooses a door. Next, (without moving the pize) Monty opens an...

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Example 7.21: Write a function to simulate categorical data

January 8, 2010
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Example 7.21: Write a function to simulate categorical data

In example 7.20, we showed how to simulate categorical data. But we might anticipate needing to do that frequently. If a SAS function weren't built in and an equivalent R function not available in a package, we could build them from scratch.SASThe SAS code is particularly tortured, since we must parse the parameter string to extract the...

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Example 7.20: Simulate categorical data

January 4, 2010
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Example 7.20: Simulate categorical data

Both SAS and R provide means of simulating categorical data (see section 1.10.4). Alternatively, it is trivial to write code to do this directly. In this entry, we show how to do it once. In a future entry, we'll demonstrate writing a SAS Macro (section A.8.1) and a function in R (section B.5.2) to do it...

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Example 7.19: find the closest pair of observations

December 28, 2009
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Example 7.19: find the closest pair of observations

Suppose we need to find the closest pair of observations on some variable x. For example, we might be concerned that some data had been accidentally duplicated. We return the ID's of the two closest observations, and their distance from each other. In both languages, we'll first create the data, then sort it, recognizing that the...

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SAS and R included on R bloggers

December 18, 2009
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SAS and R included on R bloggers

The R bloggers site is an aggregator for blogs about R. We're excited to be joining that community and suggest any readers of this blog may also find it useful.

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Example 7.18: Displaying missing value categories in a table

December 14, 2009
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Example 7.18: Displaying missing value categories in a table

When displaying contingency tables (section 2.3.1), there are times when it is useful to either show or hide the missing data category. Both SAS and the typical R command default to displaying the table only for observations where both factors are observed.In this example, we generate some multinomial data (section 1.10.4) and then produce tables with and without...

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