R Course: Lesson 6, Part 2

In the last part of Page‘s R course we will continue learning about LMEMs by using contrast coding and model comparison. We will also extended our use of inline R code in an R Markdown document.

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R Course: Lesson 6, Part 1

It has been a while, but we’re happy to present the last two parts of Page’s R course. In this lesson we will learn how to run a LMEM (linear mixed effects model). We will also introduce the packages RColorBrewer and lme4, and as always expanded your knowledge of dplyr and ggplot2 calls.

Continue reading R Course: Lesson 6, Part 1

R Course: Lesson 4

Today we’ll learn how to take an old statistics test (logistic regression) but expand it to when you have two variables (multiple regression). The package purrr is introduced and, as always, we’ll expand our knowledge of dplyr and ggplot2.

For full materials, see the course website for Lesson 4.

Here you can revisit Lesson 0, Lesson 1Lesson 2, and Lesson 3.

Continue reading R Course: Lesson 4

R Course: Lesson 2

Guest post by Page Piccinini

With some basics under our belt from Lesson 1, in this lesson we’ll continue working with dplyr and ggplot2, while also learning about the math behind linear regression and how to implement it in R. Plus you get to finish with a report about how the popularity of your name changes over time.

For full materials, see the course website for Lesson 2.

Here you can revisit Lesson 0 and Lesson 1.

Continue reading R Course: Lesson 2

R Course: Lesson 1

Guest post by Page Piccinini

In this lesson you will be introduced to the basics of R, including how to read in and manipulate data with dplyr, and how to make figures with ggplot2. You’ll also get experience writing up your results in an R Markdown document. Finally, we’ll put all of that initial set-up to good use by saving everything to Git and pushing it up to Bitbucket for better version control management.

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R Course: Lesson 0

Guest post by Page Piccinini

After telling you about my R imposter syndrome two weeks ago, I will start sharing my R course material with you here, beginning with the first lesson (well, Lesson 0) today.

This lesson is meant to set up your R working environment and get you familiar with RStudio, Git, and Bitbucket. This lesson does not include any substantial coding in R, but will situate you for productive R coding, including creating separate working environments for different projects and version control for any scripts. With these practices in place you will be a more productive R programmer in the long run, whether you are working alone or with other researchers.

Continue reading R Course: Lesson 0

An ARdent R UseR’s StoRy

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Guest post from Page Piccinini (postdoc at École Normale Supérieure, Paris)

I’ve been an R user for about 8 years (with the occasional break, including that year I took off from science and worked as a real estate agent’s personal assistant). Recently I’ve started teaching an informal R course in our department*. How I went from being self-taught to teaching a course was the prompt for this blog post. Honestly though, it feels weird to say that I’m an R programmer, I guess because I feel like it’s been ingrained in me that I’m not really an R programmer. I don’t do the most complicated things. There are so many people who know so much more than me. I’ve spent a lot of time thinking about this disconnect, the fact that people come to me to ask for help in R and I (almost) always have an answer, yet I’ll still have those moments of panic where I think I’m doing everything wrong. I’ve decided my impostor syndrome can be reduced to a couple key issues in how coding is taught and treated inside and outside of academia. First is gender discrimination. This isn’t a new idea, plenty of women have discussed gender discrimination they’ve experienced in science and the tech industry. Second is how people outside of my field (Linguistics) view my field. And third, and probably the most unfortunate of the three, is how people within my field (and potentially science at large) treat each other when it comes to coding and statistics.

Continue reading An ARdent R UseR’s StoRy