<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>Blogs on Linn Sofie Sæther</title>
    <link>https://linnsofies.netlify.app/blog/</link>
    <description>Recent content in Blogs on Linn Sofie Sæther</description>
    <generator>Hugo -- gohugo.io</generator>
    <language>en</language>
    <lastBuildDate>Thu, 08 Jun 2023 00:00:00 +0000</lastBuildDate><atom:link href="https://linnsofies.netlify.app/blog/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>Raincloud plots in R</title>
      <link>https://linnsofies.netlify.app/blog/raincloudplot_tutorial/</link>
      <pubDate>Thu, 08 Jun 2023 00:00:00 +0000</pubDate>
      
      <guid>https://linnsofies.netlify.app/blog/raincloudplot_tutorial/</guid>
      <description>What are raincloud plots and why use them? Link to heading Raincloud plots are very cool, informative and transparent visual representations of your data. Barplots and boxplots have been widely criticized as they do not show underlying patterns in the data (distribution, raw data). Raincloud plots have emerged as a way of overcoming such challenges &amp;ndash; we can visualize raw data points, the distribution and summary statistics simultaneously. In my opinion it is more intuitive and transparent, and I have to add, it also looks beautiful.</description>
    </item>
    
    <item>
      <title>Canonical Correlation Analysis (CCA) in R</title>
      <link>https://linnsofies.netlify.app/blog/cca_tutorial/</link>
      <pubDate>Fri, 02 Jun 2023 00:00:00 +0000</pubDate>
      
      <guid>https://linnsofies.netlify.app/blog/cca_tutorial/</guid>
      <description>What is CCA? Link to heading When our statistician recommended we use a CCA on our data, I have to admit I had never heard of it before. I was surprised to find out that it is a very powerful alternative to running several multivariate regressions or dimension reduction techniques like Principal Component Analysis (PCA) or Independent Component Analysis (ICA), which can sometimes be challenging to interpret.
Canonical Correlation Analysis (CCA) is similar to PCA, but with some important differences.</description>
    </item>
    
    <item>
      <title>Interactive plots with Plotly (coming!)</title>
      <link>https://linnsofies.netlify.app/blog/interactive_plotly/</link>
      <pubDate>Mon, 15 May 2023 19:42:35 +0200</pubDate>
      
      <guid>https://linnsofies.netlify.app/blog/interactive_plotly/</guid>
      <description>Tutorial is on the way.</description>
    </item>
    
  </channel>
</rss>
