Rohan Alexander and Monica Alexander join us for Talking Data Equity!
Questions, comments and the recording of the session will be posted here!
Resources for visualizing uncertainty in data a little more dynamically: Shiny - Gallery
From Manuela Marolla: “Tableau and Power Bi are excellent tools to create this type of interactive dashboards. On public.tableau.com, Discover section, you can find great examples.”
From Zelle Allyson Crawford:
“A relatively rare example of BIPOC community-led action on this issue: https://www.rootsbirthcenter.com/ What I’m concerned about is the timeline for knowledge to action in the US re maternal/nn mortality given current and long-standing data issues. Despite the gaps, how much “good data” do we need in order to act & move resources toward better health outcomes? Systems barriers to public health are often functioning as ultimately intended."
Naomi is the Deputy Director and LGBTQ Program Director at Movement Advancement Project (MAP) and she joined us to talk progress and policy-making with LGBTQI data in the USA.
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Special Guest: Aliya Bean, specialist at Manatt Health Strategies, will join us to share her work on to reproductive health and health care policy and data equity.
When will a recording of this be made available? Thank you so much!!
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Thanks for the reminder, I’m not sure how we missed it but I’ll get it up here asap! 
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Special Guest: Sara Jaye Sandford, Epidemiologist at Public Health – Seattle & King County, will join us to share her work on data biographies and data equity.
Join Heather Krause for an “Ask Me Anything” about all things data equity!
We had an excellent talk about p-values, group size, null vs nil hypothesis and all the rest! Watch the video here:
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So how do we address the issue of small group sizes? As in your example on pay equity, often the group that is experiencing inequities is the smaller group.
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Hey @Stacey this is indeed the fundamental question. How to deal with the situation of small group sizes is going, as always, to depend on the specific of the question you’re trying to answer with the data.
However, bottom line in terms of p-values and small group sizes is that we really cannot use p-value as the only criteria to decide if a difference between two groups “is real” or “matters”. It’s just not possible to do it this way if we’re trying to embed equity in the work.
As you say, a lot of the time, the smaller group is experiencing inequities and to then put an even higher “burden of proof” on this small group for us to thing that the difference matters is really doubling down on the problem our data project is likely to address.
One alternative is to use the actual size of the difference (sometimes called the effect size) as the criterion.
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Data Amnesty! The September 9th episode of Talking Data Equity was a data amnesty version. This is when Heather hosts and you can anonymously submit questions you feel are “silly” or “embarrassing” or “too beginning.” (They are not )
Here is the recording
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Talking Data Equity with Kristin Powell, Deputy Director of Black Futures Lab on their Black Census Project.
Talking Data Equity with Dr. Jessica Cerdeña: Towards Race-conscious medicine
