updating DOIs and thumbnails

Author: iramler

esports/league-of-legends-buffing-nerfing/League_of_Legends_2019_vector.svg.png

@@ -17,6 +17,7 @@ date: February 21 2024
 description: Investigating game play statistics for League of Legends champions in two different patches.
 editor: 
   canonical: true
+image: League_of_Legends_2019_vector.svg
 categories:
   - outliers
   - summary statistics

esports/league-of-legends-buffing-nerfing/index.qmd

@@ -15,7 +15,8 @@ author:
     affiliation:
     - ref: slu
 editor: 
-  canonical: true      
+  canonical: true  
+image: mens_lacrosse_faceoffs.avif    
 categories:
   - Hypothesis testing
   - Single proportion

lacrosse/college_lacrosse_faceoffs/index.qmd

@@ -19,13 +19,17 @@ author:
     - ref: slu   
 editor: 
   canonical: true
+image: pll_vs_nll.png
 categories:
   - Difference in two means
 ---
 
-## Module
+<!--
+image source
+
+https://www.insidelacrosse.com/article/breaking-pll-and-mll-to-merge-unifying-pro-outdoor-lacrosse-leagues/57087
+-->
 
-Please note that these material have not yet completed the required pedagogical and industry peer-reviews to become a published module on the SCORE Network. However, instructors are still welcome to use these materials if they are so inclined.
 
 ### Introduction
 

lacrosse/college_lacrosse_faceoffs/mens_lacrosse_faceoffs.avif

@@ -14,12 +14,19 @@ author:
   - name: Jack Fay
     affiliation:
     - ref: slu
+image: NASCAR_practice.jpg
 categories:
   - Linear regression
   - Transformations
   - Polynomial regression
 ---
 
+<!--
+image source
+
+By U.S. Air Force photo by Larry McTighe - <a rel="nofollow" class="external text" href="https://web.archive.org/web/20070321030941/http://www.af.mil/shared/media/photodb/photos/040211-F-9586M-001.jpg">United States Air Force</a>, Public Domain, <a href="https://commons.wikimedia.org/w/index.php?curid=566736">Link</a>
+-->
+
 [![](https://www.nascar.com/wp-content/uploads/sites/7/2021/06/14/9-crossover-18.gif){target="_blank" fig-alt="Stock cars used in NASCAR" fig-align="center" width="50%"}](https://www.nascar.com/gallery/best-gifs-from-2021-all-star-race-weekend/)
 
 ### Introduction
@@ -105,3 +112,11 @@ Download data: [nascar_driver_statistics.csv](nascar_driver_statistics.csv)
 ::: {.callout-note collapse="true" title="Conclusion" appearance="minimal"}
 In conclusion, the Transforming NASCAR Driver Data worksheet offers valuable insights into the relationship between average position and driver rating in NASCAR. Through the transformation of the average position variable, the worksheet enables students to enhance linearity in their models, thereby improving the accuracy of their predictions and analysis. The identification of curvature in the variable relationship also allows for the model using quadratic regression to be highly effective. The model can be conceptually compared to the model using a square root transformation to capture the same curve. Assessing the effectiveness of each model, students can critically evaluate the different approaches and determine the most suitable model for the data. This exercise equips students with essential data transformation and modeling skills, empowering them to make informed decisions and gain a deeper understanding of the factors influencing a driver's performance.
 :::
+
+### How to Cite
+
+If you use this module in your work, please cite it as follows:
+
+Bigness, A., Ramler, I & Fay, J.  (2024, August 14). Transforming NASCAR Driver Data. "The SCORE Network." https://doi.org/10.17605/OSF.IO/UQA2D
+
+You can include this citation directly in your references or bibliography.

lacrosse/lacrosse_pll_vs_nll/index.qmd

@@ -103,3 +103,14 @@ In conclusion, the Triathlon Multiple Linear Regression worksheet has provided v
 
 However, when both Swim Times and Bike Times were included as predictors in the multiple linear regression model, we observed a change in significance. Swim Times were no longer a significant predictor. This finding suggests that when considering both predictors simultaneously, the predictive power of Swim Times in estimating run times diminishes. These findings emphasize the importance of evaluating multiple predictors in regression analysis and understanding how their inclusion can impact the significance and interpretation of individual predictors.
 :::
+
+
+
+## How to Cite
+
+If you use this module in your work, please cite it as follows:
+
+Dykstra, A. J. & Ramler, I   (2024, August 14). Ironman Triathlon (Canadian Females) Multiple Regression. "The SCORE Network." https://doi.org/10.17605/OSF.IO/4MRBT.
+
+You can include this citation directly in your references or bibliography.
+