# 2330 search results for "ggplot2"

## Lies, Damn Lies, “Data Journalism” and Charts That Don’t Start at 0

January 28, 2014
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This tweet by @moorehn (who usually is a superb economic journalist) really bugged me: Alarming chart of employment for people between 25 and 54. It's like a ski jump. #SOTUecon pic.twitter.com/KNGYmwI88C— Heidi N. Moore (@moorehn) January 29, 2014 I grabbed the raw data from EPI: (http://www.epi.org/files/2012/data-swa/jobs-data/Employment%20to%20population%20ratio%20(EPOPs).xls) and properly started the graph at 0 for the

## Quantitative Finance Applications in R – 3: Plotting xts Time Series

January 28, 2014
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by Daniel Hanson, QA Data Scientist, Revolution Analytics Introduction and Data Setup Last time, we included a couple of examples of plotting a single xts time series using the plot(.) function (ie, said function included in the xts package). Today, we’ll look at some quick and easy methods for plotting overlays of multiple xts time series in a single...

## Expected overestimation of Cohen’s d under publication bias

January 27, 2014
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Earlier this week I read this article about “Why Publishing Everything Is More Effective than Selective Publishing of Statistically Significant Results” by Mercal et al (2014). The authors simulated different meta-analytic scenarios and came to the conclusion that publishing everything is more effective for the scientific collective. This got me thinking about...

## Expected overestimation of Cohen’s d under publication bias

January 27, 2014
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$Expected overestimation of Cohen’s d under publication bias$

In this post I will use the theoretical and empirical sampling distribution of Cohen's d to show the expected overestimation due to selective publishing. I will look at the overestimation for various sample sizes when the population effect is 0, 0.2, 0.5 and 0.8. The conclusion is that you should be weary of effect sizes from small samples, and...

## An idiot learns Bayesian analysis: Part 1

January 25, 2014
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I've done a dreadful job of reading The Theory That Would Not Die, but several weeks ago I somehow managed to read the appendix. Here the author gives a short explanation of Bayes' theorem using statistics related to breast cancer and mammogram results. This is the same real world example (one of several) used by

## Shoot The Heart With Monte Carlo

January 23, 2014
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The heart has its reasons which reason knows not (Blaise Pascal) You only need two functions to draw a heart mathematically. The upper part is generated by (1-(|x|-1)2)1/2 and the lower one by acos(1-|x|)-PI. Here is how this heart is: Whats the area of this heart? It’s easy: integrating heart.up(x)-heart.dw(x) between -2 and 2 and

## Plain Text, Papers, Pandoc

January 22, 2014
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Over the past few months, I’ve had several people ask me about the tools I use to put papers together. I maintain a page of resources somewhat grandiosely headed “Writing and Presenting Social Science”. Really it just makes public some configuration files and templates for my text editor and related tools. Things have changed a little recently—which led...

## Plain Text, Papers, Pandoc

January 22, 2014
By

Over the past few months, I’ve had several people ask me about the tools I use to put papers together. I maintain a page of resources somewhat grandiosely headed “Writing and Presenting Social Science”. Really it just makes public some configuration files and templates for my text editor and related tools. Things have changed a little recently—which led...

## The performance of dplyr blows plyr out of the water

January 22, 2014
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Together with many other packages written by Hadley Wickham, plyr is a package that I use a lot for data processing. The syntax is clean, and it works great for breaking down larger data.frame‘s into smaller summaries. The greatest disadvantage… See more ›

## Using One Programming Language In the Context of Another – Python and R

January 22, 2014
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Over the last couple of years, I’ve settled into using R an python as my languages of choice for doing stuff: R, because RStudio is a nice environment, I can blend code and text using R markdown and knitr, ggplot2 and Rcharts make generating graphics easy, and reshapers such as plyr make wrangling with data