My goal was to learn GitHub and integrate it with RStudio, which I did with the help of Group 4 (yay Group 4!). I also planned to follow the first steps of the reproducicibility plan, namely:
There is not much to record in my steps in installing GitHub, but I did use this website to help me out: https://happygitwithr.com/index.html
There were a lot of steps in integrating GitHub with RStudio, but with the help of Victor from Group 4 (whoop Group 4), we were all able to use GitHub through RStudio.
However, I had a few missteps with integrating GitHub. When I tried making a test repository through RStudio, I was told that there was “no path” to GitHub. Luckily, Google was on my side and I was able to figure it out.
Other than that, it was very simple to create a GitHub account and follow the website’s tutorials to understand repositories, branches, and so on.
I’m excited to start using GitHub for our assignment! I think it’s a really cool collaborative tool.
The CSV was relatively easy to find. I googled *Nichols AD, Lang M, Kavanagh C, Kundt R, Yamada J, Ariely D, et al. (2020) Replicating and extending the effects of auditory religious cues on dishonest behavior. PLoS ONE 15(8): e0237007. osf", found it on OSF and downloaded the CSV.
# Load Library
library(tidyverse)
# Read Nichols et al. CSV
nichols <- read_csv(file = "nichols/Nichols_et_al_dataset_V2.0.csv")
# Cleaning names
nichols %>%
as_tibble() %>%
clean_names()
glimpse(nichols)
After downloading the csv and reading it, I also cleaned up the data.
When I used the function “glimpse”, this is what I had:
Rows: 460
Columns: 35
$ include <dbl> 0, 0, ~
$ site <dbl> 1, 1, ~
$ id <dbl> 1, 2, ~
$ con <dbl> 4, 3, ~
$ claim <dbl> 0.0000~
$ moneyclaim <chr> "$4.51~
$ `completion time (practice included)` <time> 00:05~
$ `completion time (payments only)` <time> 05:20~
$ CT <dbl> 0.6181~
$ CT_cheat <dbl> NA, 0.~
$ sex <dbl> 0, 1, ~
$ age <dbl> 21, 33~
$ relig <dbl> 2, 1, ~
$ affil <dbl> 1, 1, ~
$ Religion <chr> "Chris~
$ `Religion Text` <chr> NA, NA~
$ affil_cong <dbl> 1, 1, ~
$ ritual <dbl> 2, 2, ~
$ religious <dbl> 7, 2, ~
$ sacred <dbl> 7, 4, ~
$ sad <dbl> 1, 1, ~
$ fast <dbl> 1, 1, ~
$ boring <dbl> 3, 3, ~
$ pleasant <dbl> 4, 4, ~
$ happy <dbl> 1, 2, ~
$ irritating <dbl> 1, 2, ~
$ slow <dbl> 4, 4, ~
$ exciting <dbl> 1, 2, ~
$ deep <dbl> 4, 1, ~
$ interesting <dbl> 1, 2, ~
$ distressing <dbl> 2, 1, ~
$ powerful <dbl> 1, 1, ~
$ relaxing <dbl> 4, 4, ~
$ distract <dbl> 1, 1, ~
$ difficult_task <dbl> 4, 4, ~
After loading the file, it was difficult for me to understand what each variable meant. A quick skim through the provided R Markdown did not provide much information either.
Some variables can be extrapolated, such as religion and affiliation, but I could not understand include or site. However, I will work with my group and read the article in more detail to figure out the rest of the variables.
Unfortunately, I did not have time to mess around and create the table due to pressing assessments I had in Week 4. The majority of my time on PSYC3361 was put into understanding GitHub and integrating it.
But, Group 4 is planning on having an online meeting tomorrow to work on it together!
I have been finding that with more workload, I have had less time working on PSYC3361. I will have to work on my time management skills, but I can imagine that being difficult since we are now in lockdown. That doesn’t mean I won’t try my best though!
My next steps are the following: