In one of our previous posts (Halloween: An Excuse for Plotting with Icons), we gave a quick tutorial on how to plot using icons using ggplot. A reader, Dr. D. K. Samuel asked in a comment how to use multiple icons. His comment read, ...can you make a blog post on using multiple icons for such data year, crop,yield 1995,Tomato,250 1995,Apple,300 1995,Orange,500 2000, Tomato,600 2000,Apple, 800 2000,Orange,900 it will be nice to use icons for each data point.

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In my course on the GLM, we are discussing residual plots this week. Given that it is also Halloween this Saturday, it seems like a perfect time to code up a residual plot made of ghosts. The process I used to create this plot is as follows: Find an icon that you want to use in place of the points on your scatterplot (or dot plot). I used a ghost icon (created by Andrea Mazzini) obtained from The Noun Project.

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This post is about ggplot2 and dplyr packages, so let’s start with loading them: library(ggplot2) library(dplyr) I can’t be the first person to make the following mistake: ggplot(mtcars, aes(x = wt, y = mpg)) %>% geom_point() Can you spot the mistake in the code above? Look closely at the end of the first line. The operator should be the + used in ggplot2 for layering, not the %>% operator used in dplyr for piping, like this:

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The other day on the isostat mailing list Doug Andrews asked the following question: Which R packages do you consider the most helpful and essential for undergrad stat ed? I ask in great part because it would help my local IT guru set up the way our network makes software available in our computer classrooms, but also just from curiosity. Doug asked for a top 10 list, and a few people have already chimed in with great suggestions.

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The term “mail merge” might not be familiar to those who have not worked in an office setting, but here is the Wikipedia definition: **Mail merge** is a software operation describing the production of multiple (and potentially large numbers of) documents from a single template form and a structured data source. The letter may be sent out to many "recipients" with small changes, such as a change of address or a change in the greeting line.

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Somehow almost an entire academic year went by without a blog post, I must have been busy… It’s time to get back in the saddle! (I’m using the classical definition of this idiom here, “doing something you stopped doing for a period of time”, not the urban dictionary definition, “when you are back to doing what you do best”, as I really don’t think writing blog posts are what I do best…)

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Yikes...It's Been Awile

Apparently our last blog post was in August. Dang. Where did five months go? Blog guilt would be killing me, but I swear it was just yesterday that Mine posted. I will give a bit of review of some of the books that I read this semester related to statistics. Most recently, I finished Hands-On Matrix Algebra Using R: Active and Motivated Learning with Applications. This was a fairly readable book for those looking to understand a bit of matrix algebra.

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Citizen Statistician

Learning to swim in the data deluge