<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Statistics on Karpoke - Just Another Blog</title><link>http://karpoke.ignaciocano.com/tags/statistics/</link><description>Recent content in Statistics on Karpoke - Just Another Blog</description><generator>Hugo -- 0.167.0</generator><language>es</language><lastBuildDate>Thu, 08 Dec 2022 14:44:15 +0100</lastBuildDate><atom:link href="http://karpoke.ignaciocano.com/tags/statistics/index.xml" rel="self" type="application/rss+xml"/><item><title>Cómo interpretar los datos sin hacerse un lío: media, mediana y moda</title><link>http://karpoke.ignaciocano.com/2022/12/08/como-interpretar-los-datos-sin-hacerse-un-lio-media-mediana-y-moda/</link><pubDate>Thu, 08 Dec 2022 14:44:15 +0100</pubDate><guid>http://karpoke.ignaciocano.com/2022/12/08/como-interpretar-los-datos-sin-hacerse-un-lio-media-mediana-y-moda/</guid><description>&lt;blockquote&gt;
&lt;p&gt;Decir que el salario medio de una población es 25 000 euros anuales no
implica que la mayoría cobre esa cantidad. Distinguir entre media,
mediana y moda es importante para interpretar los datos que aparecen en
las noticias.&lt;/p&gt;
&lt;/blockquote&gt;
&lt;p&gt;» Luis José Rodríguez Muniz | &lt;a href="https://theconversation.com/como-interpretar-los-datos-sin-hacerse-un-lio-media-mediana-y-moda-167486"&gt;theconversation.com&lt;/a&gt;&lt;/p&gt;</description></item><item><title>Netflix: A Culture of Learning</title><link>http://karpoke.ignaciocano.com/2022/01/27/netflix-a-culture-of-learning/</link><pubDate>Thu, 27 Jan 2022 20:57:42 +0100</pubDate><guid>http://karpoke.ignaciocano.com/2022/01/27/netflix-a-culture-of-learning/</guid><description>&lt;blockquote&gt;
&lt;p&gt;Netflix: A Culture of Learning&lt;/p&gt;
&lt;/blockquote&gt;
&lt;p&gt;» netflixtechblog.com | &lt;a href="https://netflixtechblog.com/netflix-a-culture-of-learning-394bc7d0f94c"&gt;netflixtechblog.com&lt;/a&gt;&lt;/p&gt;</description></item><item><title>Analyzing Episode Data for The Office Series with the Wolfram Language</title><link>http://karpoke.ignaciocano.com/2021/09/18/analyzing-episode-data-for-the-office-series-with-the-wolfram-language/</link><pubDate>Sat, 18 Sep 2021 21:38:17 +0100</pubDate><guid>http://karpoke.ignaciocano.com/2021/09/18/analyzing-episode-data-for-the-office-series-with-the-wolfram-language/</guid><description>&lt;blockquote&gt;
&lt;p&gt;Important results of a quantitative analysis of The Office TV show. See
how the dataset was created, cleaned and calculated. Inspired by Tim
Marcin&lt;/p&gt;
&lt;/blockquote&gt;
&lt;p&gt;» blog.wolfram.com | &lt;a href="https://blog.wolfram.com/2021/09/17/analyzing-episode-data-for-the-office-series-with-the-wolfram-language/"&gt;blog.wolfram.com&lt;/a&gt;&lt;/p&gt;</description></item><item><title>Estadística y fraude electoral: lo que el teorema central del límite nos revela acerca del régimen de Putin</title><link>http://karpoke.ignaciocano.com/2020/09/12/estadistica-y-fraude-electoral-lo-que-el-teorema-central-del-limite-nos-revela-a/</link><pubDate>Sat, 12 Sep 2020 20:57:00 +0100</pubDate><guid>http://karpoke.ignaciocano.com/2020/09/12/estadistica-y-fraude-electoral-lo-que-el-teorema-central-del-limite-nos-revela-a/</guid><description>&lt;blockquote&gt;
&lt;p&gt;Este domingo se celebrarán en Rusia elecciones locales. Es fácil
anticipar lo que ocurrirá. La oposición denunciará, una vez más, la
existencia de fraude electoral y divulgará multitud de videos
incriminatorios. Sin embargo, la comisión electoral ignorará las
protestas y…&lt;/p&gt;
&lt;/blockquote&gt;
&lt;p&gt;» Manuel Bagues | &lt;a href="https://nadaesgratis.es/bagues/estadistica-y-fraude-electoral-lo-que-el-teorema-central-del-limite-nos-revela-acerca-del-regimen-de-putin"&gt;nadaesgratis.es&lt;/a&gt;&lt;/p&gt;</description></item><item><title>Statistical functions in MySQL</title><link>http://karpoke.ignaciocano.com/2012/07/14/statistical-functions-in-mysql/</link><pubDate>Sat, 14 Jul 2012 19:38:00 +0100</pubDate><guid>http://karpoke.ignaciocano.com/2012/07/14/statistical-functions-in-mysql/</guid><description>&lt;blockquote&gt;
&lt;p&gt;Even in times of a growing market of specialized NoSQL databases, the
relevance of traditional RDBMS doesn’t decline. Especially when it
comes to the calculation of aggregates based on complex data sets that
can not be processed as a batch like Map&amp;amp;Reduce. MySQL is already
bringing in a handful of aggregate functions that can be useful for a
statistical analysis. The best known of this type are certainly:&lt;/p&gt;
&lt;pre&gt;&lt;code&gt;COUNT(x), SUM(x), AVG(x), MIN(x), MAX(x), STD(x)
&lt;/code&gt;&lt;/pre&gt;
&lt;p&gt;In addition, there are a number of statistical evaluations which are
also worthwhile - if not even more interesting and meaningful, but
with MySQL only producible with greater efforts. What about the
different averages? The harmonic average, a weighted average or the
geomean? What is in the course of this with the aggregate product? How
do we determine the mode, the median? The covariance?&lt;/p&gt;
&lt;p&gt;In the following article I want to go to the bottom of these questions
and develop a list of standard formulas for a statistical evaluation.
Presumably the article is meant more for beginners. In addition, a few
new features have been poured into my infusion UDF, which simplifies
some of the calculations. You can check out the source of the UDF on
Github:&lt;/p&gt;
&lt;/blockquote&gt;</description></item></channel></rss>