Inspired by Dan Quintana's "Uses This" interview, I thought it would be useful to keep a record of the tools and resources I have found helpful during my PhD. I'm writing this because maybe others would find it helpful too, but also from a selfish reason - I keep coming across a lot of great resources, and I don't have a space to write them down, so I forget about them. I will keep updating this list, as I come across more cool stuff.
I recently upgraded to a 2020 Macbook Air. Is it pretty? Yes. But is it powerful enough to deal with running a bunch of analyses and having loads of tabs open .... no. It overheats very quickly, so I use Mac Fan Control to manually change the speed of the fan if needed, and NoMachine to remote access my work computer (which is how I perform all my computationally intensive analyses).
I used to do my analyses on SPSS, but have moved to R (using it through RStudio). The resources that I used to get started with it are available for free online: R for data science, YaRrr! The pirate's guide to R, and two stats books: Danielle Navarro's Learning Statistics with R, and Andy Field's Discovering Statistics Using R (only one that's not free). I mostly use RMarkdown, which is great for compiling all your code and results into a PDF that you can then share with your collaborators.
I haven't yet gotten to that, but I'm planning to learn to use Binder, so I can share my code in an interactive, reproducible way.
For those who are still wary of making the plunge to R, JASP and Jamovi are great alternatives (with user interface similar to SPSS). We have a great tutorial on how to use them on the RIOT Science Club Youtube page.
Figures and illustrations
I do all my figures in ggplot (using R). Even if you're not fully converted to R for your analysis, you can still easily use it for your figures. Once you learn how to load your data into R, there are a lot of resources for easily making plots; here are some great one for scatterplots, histograms, or violin plots. A super fun way to learn how to plot is taking part in Tidy Tuesday and for extra motivation and fun, you can choose to make your plots using colour palettes from Harry Potter or Game of Thrones (or any others you can find - the world is your oyster).
Something else that's on my list but haven't yet used is Biorender, which has a huge library that you can use for scientific figures.
For more diverse illustrations of people (other than the standard clip art stuff), I use https://www.blackillustrations.com/
Other cool resources for ggplot visualisation are from: BBC cookbook ,
I typically write my manuscripts in Word, and email them around to my collaborators, but it's not ideal and very time-consuming (especially when getting feedback on a paper with 5+ coauthors). I tried to use Google Docs, but the conversion from word doc to google doc and back can be a bit iffy and cause you to loose formatting. I'm still looking for the ideal solution (planning to give Simul a try, as it's supposedly good for version control).
Citation manager and keeping up with literature
I recently started using Zotero as my citation manager, and really enjoying it (before I did all my references manually, which I quickly discovered was not feasible for a thesis). I found it intuitive to use, but Laura Skillen wrote a great blog on how to incorporate it in your workflow. It makes it REALLY easy to extract papers from journal websites and warns you if they've been retracted. If you're just getting started with your PhD now, start using a citation manager (otherwise you'll end up like me, in your 3rd year, manually inputting 671 references).
To find papers, I sometimes use https://www.connectedpapers.com/, which produces a visual graph for all papers that are related to one initial paper (i.e. citations etc)
I love using Slack (and Mattermost, an open source Slack alternative) instead of email. It makes it a lot easier to keep track of different projects, and to ask quick questions without the need for the formal nature of an email.
For social interactions with colleagues (during the pandemic), I love Gathertown, where you can organize virtual gatherings using avatars and cameras.
I use Google Calendar to keep track of my meetings, which I've synced up to ItsyCal (which is a tiny menu bar calendar on Mac).
I cannot even begin to explain how amazing Trello is. It's a very visual task-manager where you can have task boards and move your tasks around (from "to do" to "doing" to 'done", sort of like post-it notes). It's great for individual work, but also amazing for collaboration, as you can share your boards with colleagues and assign tasks to each other.
There are a lot of really cool tiny websites or resources that I've come across, which are helpful for both understanding stats concepts better, or for teaching them.
A really cool website to help you visualise Cohen's d effect sizes
www.guessthecorrelation.com An awesome game to help you understand how different correlation coefficients actually look as a scatterplot.
A (you guessed it: really cool) website to help you visualise the positive predictive value of the p value
(I will continue this list without repeating how cool these are, but please believe me when I say they're all awesome).
www.statcheck.io. A website that can help you detect errors in statistical reporting.
www.p-curve.com A visual aid to help you understand the flaws of the p value
Podcast and Youtube
Finding collaborators, speakers, and researchers to cite
Spreadsheet of BIPOC-authored Psychology Papers
Other helpful miscellaneous stuff