what i learned at positconf

Several weeks ago I attended #positconf in Seattle. I was super grateful to receive funding for my travel, stay, and registration from Posit as an Opportunity Scholar and now that I have had some time to reflect, I wanted to share some takeaways from the experience, in case they are beneficial to people who might be trying to decide whether to apply to go next year. The Opportunity Scholar program is a really great way to diversify the attendees at the conference, but there is no point inviting people from under-represented communities to attend if you don’t also do the much more difficult work of creating a space where they feel welcome.

learning python outloud

When you are exploring a far off land and only know a tiny bit of the language they speak there, you ALWAYS carry a little dictionary with commonly used phrases translated from the language you speak into the other language. It is important to know how to ask someone where the toilets are while you are travelling! I have just started learning Python with Posit Academy in the lead up to #positconf2024 and I am trying to approach in the same way I would if I was learning French.

rowwise %>% mean

Series: IDHTG

When you have data from a survey, the responses for each item are most often listed in different variables. Generally you have to average across the items to get a mean value for that scale for each participant. But dealing with calculations across rows is sometimes difficult in R. load packages + make some data library(tidyverse) pID <- c("p1", "p2", "p3", "p4", "p5", "p6") item1 = sample(1:7, 6, replace=T) item2 = sample(1:7, 6, replace=T) item3 = sample(1:7, 6, replace=T) item4 = sample(1:7, 6, replace=T) item5 = sample(1:7, 6, replace=T) survey <- data.

how to do t-tests

Series: IDHTG

I was trying to work out how to do t-tests using my own data and the lsr package but ended up working with Dani’s AFL data from her book while trying to work out why R insisted that my outcome variable wasn’t numeric (it definitely was). Turns out that the lsr package doesn’t deal well with tibbles (which are created by default when you use read_csv to get your data) but if you use read.

error bars on plots

Series: IDHTG

Repurposing this APA figures post as a IDHTG post. As I write my first paper reporting data analysis coming out of R (woot!!!), here are some notes summarising all the googling I have done this morning about how to produce APA style figures in ggplot. Load libraries Start by loading tidyverse to get ggplot, here to make finding the data easy, and papaja to get the theme_apa() function.