Full draft of ep 4 (and rough draft of ep 5) #95
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kaijagahm
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episode:reproducible code
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| #### Welcome and introductions | |||
| - Welcome to "RRRR, I'm Stuck!" We're glad you're here! Let's first take care of a few setup steps. You should have all followed the setup instructions on the [workshop website](kaijagahm.github.io/R-help-reprexes/), and you should have both R and RStudio installed. | |||
| - Welcome to "RRRR, I'm Stuck!" We're glad you're here! Let's first take care of a few setup steps. You should have all followed the setup instructions on the [workshop website](https://carpentries-incubator.github.io/R-help-reprexes/), and you should have both R and RStudio installed. | |||
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| - You should also have the following packages installed: {**reprex**}, {**ratdat**}, {**dplyr**}, and {**ggplot2**}. | |||
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should probably add package versions or have an renv tie-in
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Comments on changes occuring previously to this pull request -- unfortunately I can't comment on the exact line :(
Line 9: How is the process of getting help in R different from getting help with other things?
I don't understand this question, and it seems somewhat vague... maybe "how can I get help with problems in my code?" and "Why are we covering R in this lesson?" Idk something along those lines?
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Line 28:
"We have a range of levels of experience here. This workshop assumes that you are researcher in ecology/biology who has some prior experience working with R in RStudio."
How much are we assuming that? I think it's fine to just say "we are ecologists and will focus on a biological example, but this is applicable to many data scientists" -- unless we want an explicit carpentries' R Ecology connection?
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I think it would be good to be very explicit with prior experience (e.g. "R skills from carpentries' R Ecology lesson" and also a bit of a verbal cheatsheet for places to skip to in case you have prior experience
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Lines 58-69: Unsure of why these lines are in code blocks. They do show up a bit weirdly on the rendered markdown / website
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Love the idea of a diagram
| - Which part of my code is causing the problem? | ||
| - Which parts of my code should I include in a minimal example? | ||
| - How can I tell whether a code snippet is reproducible or not? | ||
| - How can I make my code reproducible? | ||
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| ::: objectives | ||
| - Explain the value of a minimal code snippet. |
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This seems a little vague and mostly redundant with previous objectives and later objectives?
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| table(rodents$taxa) | ||
| You're happy with the progress you've made in exploring your data, and you're excited to move on to your second research question: Do the k-rat exclusion plots actually exclude k-rats? |
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We should probably describe krats more in depth in the intro, and make sure our predictions and tests are the simplest questions we can ask, just to not add too much to cognitive load
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| # Not very helpful. BUT | ||
| sum(is.na(rodents$taxa)) # sum considers T = 1 and F = 0 | ||
| Prediction 1: If the k-rat plots work, then we would expect to see fewer k-rats in the k-rat exclusion plots than in the control, with the fewest in the long-term k-rat exclosure plot. |
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I feel like prediction / hypothesis can intrinsically condition on 'working'.
How about "Prediction 1: Fewer k-rats occupy k-rat exclosure plots than control plots; Prediction 2: Fewer k-rats occupy long-term k-rat exclosure plots than either control or short-term exclosure plots"
| rodents <- rodents %>% | ||
| filter(taxa == "Rodent") | ||
| glimpse(rodents) | ||
| Second, if the k-rat plots work, then we would expect a lower proportion of *spectabilis* in the *spectabilis*-specific exclosure than in the control plot, regardless of the absolute number of k-rats caught. |
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"Prediction 3: A lower proportion of spectabilis occupy the spectabilis-specific exclosure than the control plot"
| # If the k-rat plots work, then we would expect: | ||
| # A. Fewer k-rats overall in any of the exclusion plots than in the control, with the fewest in the long-term k-rat exclusion plot | ||
| ```{r} | ||
| # Prediction 1: expect fewer k-rats in exclusion plots than in control plot |
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Whoops, I guess it gets simplified down here
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Source : 4afb5eb
Branch : main
Author : peterlaurin <[email protected]>
Time : 2024-12-31 21:58:11 +0000
Message : Merge pull request #95 from carpentries-incubator/accept-xor-changes-ep4
Full draft of ep 4 (and rough draft of ep 5)
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Source : 7dd2930
Branch : md-outputs
Author : GitHub Actions <[email protected]>
Time : 2024-12-31 22:00:42 +0000
Message : markdown source builds
Auto-generated via `{sandpaper}`
Source : 4afb5eb
Branch : main
Author : peterlaurin <[email protected]>
Time : 2024-12-31 21:58:11 +0000
Message : Merge pull request #95 from carpentries-incubator/accept-xor-changes-ep4
Full draft of ep 4 (and rough draft of ep 5)
@xortizross @peterlaurin
Re-drafted the reproducible code episode.
Created a really really rough draft of the "asking your question" episode. Organization/flow of that one needs some help but I wanted to brain dump.
This content is ready for review (and it really needs it!!!)