Adding more description of the stats module framing to the 'overview'…

… section

_freeze/mod_stats/execute-results/html.json

@@ -1,11 +1,9 @@
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-    "markdown": "---\ntitle: \"Analysis & Modeling\"\ncode-annotations: hover\n---\n\n\n## Overview\n\nGiven the wide range in statistical training in graduate curricula (and corresponding breadth of experience among early career researchers), we'll be approaching this module in a different way than the others. One half of the module will use a \"flipped approach\" where project teams will share their proposed analyses with one another. The other half of the module will be dedicated to analyses that are more common in--or exclusive to--synthesis research.\n\n## Learning Objectives\n\nAfter completing this module you will be able to: \n\n- <u>Describe</u> proposed analytical methods to an interested audience of mixed prior experience\n- <u>Explain</u> nuance in interpretation of results of proposed analyses\n- <u>Compare</u> and contrast interpretation of results in synthesis work versus primary research\n- <u>Identify</u> statistical tests common in synthesis research\n- <u>Perform</u> some synthesis-specific analyses\n\n## Needed Packages\n\nIf you'd like to follow along with the code chunks included throughout this module, you'll need to install the following packages:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Note that these lines only need to be run once per computer\n## So you can skip this step if you've installed these before\ninstall.packages(\"tidyverse\")\n```\n:::\n\n\n## Mixed-Effects Models\n\n\n\n## Multi-Model Inference\n\n\n\n## Meta-Analysis\n\n\n\n## Additional Resources\n\n### Papers & Documents\n\n- [Understanding ‘It Depends’ in Ecology: A Guide to Hypothesising, Visualising and Interpreting Statistical Interactions](https://onlinelibrary.wiley.com/doi/10.1111/brv.12939). Spake _et al._, 2023. **Biological Reviews** \n- [Improving Quantitative Synthesis to Achieve Generality in Ecology](https://www.nature.com/articles/s41559-022-01891-z). Spake _et al._, 2022.**Nature Ecology and Evolution**\n- [Doing Meta-Analysis with R: A Hands-On Guide](https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/)\n\n### Workshops & Courses\n\n- Matt Vuorre's [Bayesian Meta-Analysis with R, Stan, and brms](https://mvuorre.github.io/posts/2016-09-29-bayesian-meta-analysis/)\n\n### Websites\n\n- \n",
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+    "markdown": "---\ntitle: \"Analysis & Modeling\"\ncode-annotations: hover\n---\n\n\n## Overview\n\nGiven the wide range in statistical training in graduate curricula (and corresponding breadth of experience among early career researchers), we'll be approaching this module in a different way than the others. One half of the module will use a \"flipped approach\" where project teams will share their proposed analyses with one another. The other half of the module will be dedicated to analyses that are more common in--or exclusive to--synthesis research. Content produced by project teams during the flipped half may be linked in the [Additional Resources](https://lter.github.io/ssecr/mod_stats.html#additional-resources) section at the bottom of this module at the discretion of each team. Otherwise the content of this module will focus only on the non-flipped content.\n\n## Learning Objectives\n\nAfter completing this module you will be able to: \n\n- <u>Describe</u> proposed analytical methods to an interested audience of mixed prior experience\n- <u>Explain</u> nuance in interpretation of results of proposed analyses\n- <u>Compare</u> and contrast interpretation of results in synthesis work versus primary research\n- <u>Identify</u> statistical tests common in synthesis research\n- <u>Perform</u> some synthesis-specific analyses\n\n## Needed Packages\n\nIf you'd like to follow along with the code chunks included throughout this module, you'll need to install the following packages:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Note that these lines only need to be run once per computer\n## So you can skip this step if you've installed these before\ninstall.packages(\"tidyverse\")\n```\n:::\n\n\n## Mixed-Effects Models\n\n\n\n## Multi-Model Inference\n\n\n\n## Meta-Analysis\n\n\n\n## Additional Resources\n\n### Papers & Documents\n\n- [Understanding ‘It Depends’ in Ecology: A Guide to Hypothesising, Visualising and Interpreting Statistical Interactions](https://onlinelibrary.wiley.com/doi/10.1111/brv.12939). Spake _et al._, 2023. **Biological Reviews** \n- [Improving Quantitative Synthesis to Achieve Generality in Ecology](https://www.nature.com/articles/s41559-022-01891-z). Spake _et al._, 2022.**Nature Ecology and Evolution**\n- [Doing Meta-Analysis with R: A Hands-On Guide](https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/)\n\n### Workshops & Courses\n\n- Matt Vuorre's [Bayesian Meta-Analysis with R, Stan, and brms](https://mvuorre.github.io/posts/2016-09-29-bayesian-meta-analysis/)\n\n### Websites\n\n- \n",
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mod_stats.qmd

@@ -5,7 +5,7 @@ code-annotations: hover
 
 ## Overview
 
-Given the wide range in statistical training in graduate curricula (and corresponding breadth of experience among early career researchers), we'll be approaching this module in a different way than the others. One half of the module will use a "flipped approach" where project teams will share their proposed analyses with one another. The other half of the module will be dedicated to analyses that are more common in--or exclusive to--synthesis research.
+Given the wide range in statistical training in graduate curricula (and corresponding breadth of experience among early career researchers), we'll be approaching this module in a different way than the others. One half of the module will use a "flipped approach" where project teams will share their proposed analyses with one another. The other half of the module will be dedicated to analyses that are more common in--or exclusive to--synthesis research. Content produced by project teams during the flipped half may be linked in the [Additional Resources](https://lter.github.io/ssecr/mod_stats.html#additional-resources) section at the bottom of this module at the discretion of each team. Otherwise the content of this module will focus only on the non-flipped content.
 
 ## Learning Objectives