Editing Data Into Insights (Spring 2021)

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* The readings this week talked a lot about how data visualizations can be misleading. How can we tell when visualizations are intentionally trying to mislead versus when they are just poorly designed?
 
* The readings this week talked a lot about how data visualizations can be misleading. How can we tell when visualizations are intentionally trying to mislead versus when they are just poorly designed?
 
* I was confused by the reading on counterfactuals. We obviously can't really know what would have happened in different conditions, so why even try?
 
* I was confused by the reading on counterfactuals. We obviously can't really know what would have happened in different conditions, so why even try?
* Imagine you were asked to create an ad campaign to recruit students to Purdue. What types of appeals would you use and why?
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* Imagine if you were asked to create an ad campaign to recruit students to Purdue. What types of appeals would you use and why?
  
 
During other weeks, we will be more focused on learning practical skills (mostly data manipulation and visualization in R). On those weeks, discussions will center around identifying places where folks are still confused and students will be randomly selected to share their responses to homework questions.
 
During other weeks, we will be more focused on learning practical skills (mostly data manipulation and visualization in R). On those weeks, discussions will center around identifying places where folks are still confused and students will be randomly selected to share their responses to homework questions.

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