---
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author: ""
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    toc-depth: 4
    toc-location: left
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# Project Setup

```{r}
#| label:  setup

source('https://inkaverse.com/setup.r')
```

# Data import

```{r}
gs <- "url" %>% 
  as_sheets_id()

fb <- gs %>% 
  range_read(ss = .,sheet = "fb")
```

# References

Broman, K. W., & Woo, K. H. (2017). Data organization in spreadsheets. The American Statistician, 72(1), 2–10. https://doi.org/10.1080/00031305.2017.1375989

Zuur, A. F., Ieno, E. N., & Elphick, C. S. (2009). A protocol for data exploration to avoid common statistical problems. Methods in Ecology and Evolution, 1(1), 3–14. https://doi.org/10.1111/j.2041-210x.2009.00001.x

Francoishusson. (2017, July 13). PCA course using FactoMineR | R-bloggers. R-bloggers. https://www.r-bloggers.com/2017/07/pca-course-using-factominer/

Kozak, M., & Piepho, H. (2017). What’s normal anyway? Residual plots are more telling than significance tests when checking ANOVA assumptions. Journal of Agronomy and Crop Science, 204(1), 86–98. https://doi.org/10.1111/jac.12220

Tanaka, E., & Hui, F. K. C. (2019). Symbolic formulae for linear mixed models. In Communications in computer and information science (pp. 3–21). https://doi.org/10.1007/978-981-15-1960-4_1

Schielzeth, H., Dingemanse, N. J., Nakagawa, S., Westneat, D. F., Allegue, H., Teplitsky, C., Réale, D., Dochtermann, N. A., Garamszegi, L. Z., & Araya‐Ajoy, Y. G. (2020). Robustness of linear mixed‐effects models to violations of distributional assumptions. Methods in Ecology and Evolution, 11(9), 1141–1152. https://doi.org/10.1111/2041-210x.13434

# Research Objective

1. 
1.

## RO 1

```{r}

```

## RO 2

```{r}

```
