<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>De Rerum Natura &#187; precision error application</title>
	<atom:link href="http://www.corrada.com/blog/category/error-theory/precision-error-application/feed/" rel="self" type="application/rss+xml" />
	<link>http://www.corrada.com/blog</link>
	<description>Randomness, entropy, pattern matching, maps, geometry, knots, and scientific readings</description>
	<lastBuildDate>Sun, 21 Aug 2011 17:38:55 +0000</lastBuildDate>
	<language>en</language>
	<sy:updatePeriod>hourly</sy:updatePeriod>
	<sy:updateFrequency>1</sy:updateFrequency>
	<generator>http://wordpress.org/?v=3.2.1</generator>
		<item>
		<title>Robust voting in uncertain environments</title>
		<link>http://www.corrada.com/blog/2008/11/17/robust-voting-in-uncertain-environments/</link>
		<comments>http://www.corrada.com/blog/2008/11/17/robust-voting-in-uncertain-environments/#comments</comments>
		<pubDate>Mon, 17 Nov 2008 05:00:15 +0000</pubDate>
		<dc:creator>Andrés</dc:creator>
				<category><![CDATA[Compressed Sensing]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[precision error application]]></category>
		<category><![CDATA[Randomness]]></category>

		<guid isPermaLink="false">http://www.corrada.com/blog/?p=83</guid>
		<description><![CDATA[Combining the judgments of different recognizers is always better than using the best one alone. This observation is universal in machine learning realms. But it seldom gets used in practice. Why? For one, it costs more to implement. Instead of one recognizer, you must deploy several. Computing cycles grow linearly with the number of recognizers [...]]]></description>
		<wfw:commentRss>http://www.corrada.com/blog/2008/11/17/robust-voting-in-uncertain-environments/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Not every measurement is perfect</title>
		<link>http://www.corrada.com/blog/2008/04/13/not-every-measurement-is-perfect/</link>
		<comments>http://www.corrada.com/blog/2008/04/13/not-every-measurement-is-perfect/#comments</comments>
		<pubDate>Mon, 14 Apr 2008 01:34:12 +0000</pubDate>
		<dc:creator>Andrés</dc:creator>
				<category><![CDATA[Multiple Choice Questions Exam]]></category>
		<category><![CDATA[precision error application]]></category>

		<guid isPermaLink="false">http://www.corrada.com/blog/?p=73</guid>
		<description><![CDATA[Just to show that not all questions behave as nicely as question 9 in the previous post, here is the plot for question 6 in the same exam.The fit is not as good as for question 9. This is expected, there is no reason why the precision error should decay with a perfect exponential behavior. [...]]]></description>
		<wfw:commentRss>http://www.corrada.com/blog/2008/04/13/not-every-measurement-is-perfect/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Minimum number of questions needed for an exam</title>
		<link>http://www.corrada.com/blog/2008/03/29/minimum-number-of-questions-needed-for-an-exam/</link>
		<comments>http://www.corrada.com/blog/2008/03/29/minimum-number-of-questions-needed-for-an-exam/#comments</comments>
		<pubDate>Sat, 29 Mar 2008 18:12:59 +0000</pubDate>
		<dc:creator>Andrés</dc:creator>
				<category><![CDATA[precision error application]]></category>
		<category><![CDATA[Randomness]]></category>
		<category><![CDATA[test assessment]]></category>

		<guid isPermaLink="false">http://www.corrada.com/blog/2008/03/29/minimum-number-of-questions-needed-for-an-exam/</guid>
		<description><![CDATA[Another application of the precision error covariance matrix is to find out the minimum number of questions needed for an exam. The linear algebra system derived from the precision erorr equations requires at least three scientific models before one can measure the precision error. More is better. But what is enough? How many questions does [...]]]></description>
		<wfw:commentRss>http://www.corrada.com/blog/2008/03/29/minimum-number-of-questions-needed-for-an-exam/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Grading mistake detection with precision error</title>
		<link>http://www.corrada.com/blog/2008/03/28/grading-mistake-detection-with-precision-error/</link>
		<comments>http://www.corrada.com/blog/2008/03/28/grading-mistake-detection-with-precision-error/#comments</comments>
		<pubDate>Fri, 28 Mar 2008 21:51:30 +0000</pubDate>
		<dc:creator>Andrés</dc:creator>
				<category><![CDATA[precision error application]]></category>
		<category><![CDATA[Randomness]]></category>
		<category><![CDATA[test assessment]]></category>

		<guid isPermaLink="false">http://www.corrada.com/blog/2008/03/28/grading-mistake-detection-with-precision-error/</guid>
		<description><![CDATA[While making a covariance matrix for eighteen questions in an introductory Physics exam I gave in the Spring of 2006, I discovered another use for the precision error measurements: grading mistake detection. The figure shown first is my initial try. I computed the student score on each question with the function: $f(\text{correct})=1.0, f(\text{incorrect})=0.0$.. Note the [...]]]></description>
		<wfw:commentRss>http://www.corrada.com/blog/2008/03/28/grading-mistake-detection-with-precision-error/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
	</channel>
</rss>

