ualg.rep.data.analysis/week8.qmd at main · instructr/ualg.rep.data.analysis · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
---
title: "Week 8 | Progress feedback one-on-one"
---

::: {.callout-note}
## Class Details
📅 **Date:** 14 May, 2025
⏰ **Time:** 14:00h - 16:00h
📖 **Synopsis:** One-on-one meeting focused on receiving feedback on the manuscript draft, the R code used for data analysis, interpretation of results, and adherence to best practices for reproducible research.
:::

:::{.panel-tabset}

### Done in Class

Books suggested to help with data analysis:

  1. *The Art of Data Science.*
Roger D. Peng and Elizabeth Matsui. 2018.
<https://leanpub.com/artofdatascience>

  2. *R for Data Science* (2e).
Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund. 2023.
<https://r4ds.hadley.nz/>

  3. *Tidy Modeling with R.*
Max Kuhn and Julia Silge. 2023.
<https://www.tmwr.org/>

  4. *Modern Statistics for Modern Biology.*
Susan Holmes and Wolfgang Huber. 2025.
<https://www.huber.embl.de/msmb/>


#### Overview of Model Classifications

![](pics/types_of_models.png)
![](pics/categories_of_models.png)

#### How Does Modeling Fit into the Data Analysis Process?

!["Based on: R for Data Science. Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund. 2023. | Tidy Modeling with R. Max Kuhn and Julia Silge. 2023."](pics/modelling_process.png)


### To Do at Home

Particular tasks for BB

1. **Refactor the data analysis script** by splitting the current single script into two separate scripts: one for *Descriptive Analysis* and one for *Modeling*.

2. **Apply the following changes to the data analysis scripts**:

   * Add the `site` variable to the tidy dataset.
   * Exclude the `id` variable from the MCA calculation.
   * Color the PCA plots using relevant categorical variables to help identify groupings.
   * Move the PCA visualization with variable vectors to the modeling script.
   * Combine the individual histograms into a single multi-panel figure.
   * Remove the printing of descriptive statistics for each variable separately; keep only the summary table with all variables described.

3. **Draft the *Scientific Data* descriptor manuscript**: Prepare a clean first draft to share with the tutor for feedback.

4. **Prepare final questions or suggestions** related to reproducible data analysis for discussion.