Skip to main content

Oooh, I hate all talk of false positive, false negative, false discovery, etc.

A correspondent writes:

I think this short post on p value, bayes, and false discovery rate contains some misinterpretations.

My reply: Oooh, I hate all talk of false positive, false negative, false discovery, etc.

I posted this not because I care about someone, somewhere, being “wrong on the internet.” Rather, I just think there’s so much wrong with so much of the scientific discourse on science and statistics and learning from data. It’s beyond Bayes or p-value or anything so specific; I think it gets to deeper issues regarding goals and expectations of certainty.

The post Oooh, I hate all talk of false positive, false negative, false discovery, etc. appeared first on Statistical Modeling, Causal Inference, and Social Science.



from Statistical Modeling, Causal Inference, and Social Science http://ift.tt/2kduodV
via IFTTT

Comments

Popular posts from this blog

Using RStudio and LaTeX

(This article was first published on r – Experimental Behaviour , and kindly contributed to R-bloggers) This post will explain how to integrate RStudio and LaTeX, especially the inclusion of well-formatted tables and nice-looking graphs and figures produced in RStudio and imported to LaTeX. To follow along you will need RStudio, MS Excel and LaTeX. Using tikzdevice to insert R Graphs into LaTeX I am a very visual thinker. If I want to understand a concept I usually and subconsciously try to visualise it. Therefore, more my PhD I tried to transport a lot of empirical insights by means of  visualization . These range from histograms, or violin plots to show distributions, over bargraphs including error bars to compare means, to interaction- or conditional effects of regression models. For quite a while it was very tedious to include such graphs in LaTeX documents. I tried several ways, like saving them as pdf and then including them in LaTeX as pdf, or any other file ...

Controlling legend appearance in ggplot2 with override.aes

[This article was first published on Very statisticious on Very statisticious , and kindly contributed to R-bloggers ]. (You can report issue about the content on this page here ) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. In ggplot2 , aesthetics and their scale_*() functions change both the plot appearance and the plot legend appearance simultaneously. The override.aes argument in guide_legend() allows the user to change only the legend appearance without affecting the rest of the plot. This is useful for making the legend more readable or for creating certain types of combined legends. In this post I’ll first introduce override.aes with a basic example and then go through three additional plotting scenarios to how other instances where override.aes comes in handy. Table of Contents R packages Introducing override.aes Adding a guides() layer Using the guide argument in scale_*() Changing multiple aesthetic par...