Welcome to the Intermediate R3 workshop!

  • ✔️ Pick a group from the basket and go to that table
  • ✔️ Introduce yourself
  • ✔️ Open your LearnR3.Rproj RStudio project
  • ✔️ Check that your data-raw/ looks like that on the right
data-raw/
├── README.md
├── mmash
│   ├── user_1
│   ├── user_10
│   ├── user_11
│   ├── ...
│   ├── user_7
│   ├── user_8
│   └── user_9
└── mmash-data.zip

Introduce teachers and helpers.

Motivation for this workshop

How do you exactly do data analysis? What’s the workflow? 🤔

When I started out doing research during my Masters, I always wondered how do researchers go about doing data analysis… what was their workflow exactly like. No one ever really taught that. Even on online tutorials, mostly pieces of code or how to use code are taught… but never teaching the bigger picture… How do researchers in their daily work write R code and do their data analysis?

This question is the reason why the overall workflow is the primary focus in this workshop and partly with the beginner one. I try to focus on the bigger picture and the overall workflow you would do for doing data analysis.

So, why is it that there isn’t much information on how researchers do data analysis?

🤷😕…Because code sharing is almost non-existent in science

Very few papers provide code (2)

It’s because code sharing basically doesn’t exist in the vast majority of scientific fields. You’ve probably read a methods section in a paper and wondered how exactly they did it.

Code sharing: From scientific principle of “reproducibility”

…often confused with “replicability” (3) (see also American Statistical Association statement)

Replicability

  • Repeating a study by independently performing another identical study
  • Linked to the “irreproducibility crisis” (aka “irreplicability crisis”)

Reproducibility

  • Generating the exact same results when using the same data and code
  • Question: If we can’t even reproduce a study’s results, how can we expect to replicate it?

These issues can be fixed by creating and nurturing a culture of openness

Goal of this workshop? Start changing the culture by providing the training

Workshop details

Setup and layout

  • Workshop is mix of:
    • “Code-alongs” (we type and explain, you type along)
    • Hands-on coding, discussing, and reading exercises
    • Dedicated practice time (potentially on your own data)
  • All material is online (and openly licensed)
  • Resources Appendix
    • Material for further learning
  • Reading tasks are “callout” blocks marked by the blue line on the left side of the text
  • Schedule listed is a guide only, some sessions are longer, others shorter
  • Less about coding, more about connecting with others
    • During lunch, try to sit beside someone you don’t know
    • Several networking activities (usually after lunch)
  • Feedback collected at end of every day, it is so helpful and important for improving the workshop 😁

Explain a bit more about the reading, why doing it, and that this workshop in particular has a lot more of it than more advanced workshops.

About feedback, will improve this workshop, we’re collaborating together to make it better. You’re learning, but also helping to improve the material and in how we teach you. What makes sense, what is confusing, and so on.

Getting or asking for help 🙋‍♀️🙋‍♂️

  • Put the origami hat on your laptop to get help
    • There are lots of helpers
    • Table mates, you can help out too
  • We’re all learning here!
    • This is a supportive and safe environment
    • Remember our Code of Conduct

Practice using origami hats: Does your data-raw/ look as this?

data-raw/
├── README.md
├── mmash
│   ├── user_1
│   ├── user_10
│   ├── user_11
│   ├── ...
│   ├── user_7
│   ├── user_8
│   └── user_9
└── mmash-data.zip

Activities

🚶🚶‍♀️ How do you perceive your skill in R?

Along the wall, arrange to one side is “novice/basic” and other side is “advanced”.

🚶🚶‍♀️ Who has had formal training in specifically coding in R or in general?

One side of the room is yes, the other side is no. Can also be in the middle if you aren’t completely sure. If the workshop was part of a statistics workshop, it doesn’t really count.

🚶‍♀️🚶 Who has struggled with using R?

One side of the room if yes, other side if no, middle if you’ve sort have struggled.

🙋 Who has seen or worked with “true” data analysis pipelines (e.g. run a single command and everything gets re-done)?

More for my personal interest. The word pipeline gets thrown around a lot, but how many have encountered, made, or used true pipelines? Automated from beginning to end.

💬 For those that have done or are doing data processing, does it take up a lot of time? How much?

Question, mostly for my own information…

Return to your seats! 🪑

References

1.
Leek JT, Jager LR. Is most published research really false? Annual Review of Statistics and Its Application. 2017 Mar;4(1):109–22.
2.
Considine EC, Thomas G, Boulesteix AL, Khashan AS, Kenny LC. Critical review of reporting of the data analysis step in metabolomics. Metabolomics. 2017 Dec;14(1).
3.
Plesser HE. Reproducibility vs. Replicability: A brief history of a confused terminology. Frontiers in Neuroinformatics. 2018 Jan;11.
Welcome to the Intermediate R 3 workshop! ✔️ Pick a group from the basket and go to that table ✔️ Introduce yourself ✔️ Open your LearnR3.Rproj RStudio project ✔️ Check that your data-raw/ looks like that on the right data-raw/ ├── README.md ├── mmash │ ├── user_1 │ ├── user_10 │ ├── user_11 │ ├── ... │ ├── user_7 │ ├── user_8 │ └── user_9 └── mmash-data.zip

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  • Welcome to the Intermediate R3 workshop!
  • Motivation for this workshop
  • How do you exactly do data analysis? What’s the workflow? 🤔
  • 🤷😕…Because code sharing is almost non-existent in science
  • Code sharing: From scientific principle of “reproducibility”
  • These issues can be fixed by creating and nurturing a culture of openness
  • Goal of this workshop? Start changing the culture by providing the training
  • Workshop details
  • Setup and layout
  • Getting or asking for help 🙋‍♀️🙋‍♂️
  • Practice using origami hats: Does your data-raw/ look as this?
  • Activities
  • 🚶🚶‍♀️ How do you perceive your skill in R?
  • 🚶🚶‍♀️ Who has had formal training in specifically coding in R or in general?
  • 🚶‍♀️🚶 Who has struggled with using R?
  • 🙋 Who has seen or worked with “true” data analysis pipelines (e.g. run a single command and everything gets re-done)?
  • 💬 For those that have done or are doing data processing, does it take up a lot of time? How much?
  • Return to your seats! 🪑
  • References
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