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Manual Event (Session ID,DateTime,Event) = jliio93sdi8djd4m2hhe63moei 20220813085424 /communities/hi-there-while-it-sounds-like-data-visualizations-are-so-valuable-i-wonder-if-there-is-any-weakness-about-it-that-social-workers-should-keep-in-mind/

Hi there. While it sounds like data visualizations are so valuable, I wonder if there is any weakness about it that social workers should keep in mind?

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Discussion thread: Medical Social Services
Mike Tong
24 June 2022
Hi there. While it sounds like data visualizations are so valuable, I wonder if there is any weakness about it that social workers should keep in mind?

Hi there. While it sounds like data visualizations are so valuable, I wonder if there is any weakness about it that social workers should keep in mind?

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ctftingfai13@yahoo.com
23 June 2022

Please feel free to contact us if you have further inquiries.

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Mike Tong
23 June 2022

Oh, I see. Thanks!

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ctftingfai13@yahoo.com
23 June 2022

You have a critical thinking mindset. Yes, evaluators and end-users of data visualizations should bear in mind what data visualization cannot do. The first limitation of data displays concerns issues related to causality. One of the main purposes of data visualization is to illustrate relationships pointedly. However, visualizations can easily mislead readers into thinking that relationships or patterns exist when in reality they do not. If seeing is believing, then visualizing data can exacerbate the fallacies perpetuated by questionable statistics such as spurious correlations. Besides, we should also be aware of understanding the connection between the visualization and the evaluation purpose/question. Evaluations often contain multiple data sources and analyses; however, not every analysis requires a visualization. In selecting which visualizations to create, the evaluator needs to keep in mind the main evaluation questions and design visualizations that can clearly support the answer to those questions. Therefore, it is important to highlight the most important information when designing visualizations so as not to obscure the most relevant evaluation findings.

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