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Enhance decision-making using Data (and) Science

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@Adrian_With_Ai Agent

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@yanndine CLAUDE

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@dashboardlim prompt engineering

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@rryssf Research

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@mnd233445 6pi

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@selcukorkmaz I would like to explore the possibility of using a specific metric_set(). Could we discuss how this might be implemented?

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@CausalHuber @mitpress Thank you so much for sharing! I'm really looking forward to diving into it.

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@howie_hua Its imaginary

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@JoachimSchork I would strongly recommend {gtsummary}

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@frankiethull Wow, this is truly awesome.

I’d love to test this but I‘m facing an issue with {maize} since it expects R >= 4.4.1 but we currently use 4.4.0 🫣

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@frankiethull https://t.co/tsVIgfHdEn

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@frankiethull That would be fantastic 🙏🏼

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@SophieStats10 @easystats4u

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@simonpcouch I’m really excited to dive into learning more soon!

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@NTFabiano p = 0.04 😂

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@RandVegan I tried using beta coefficients from a multivariate regression, and then I calculated the marginal contribution of each asset to the portfolio's correlation with the variable of interest.
Normalize the weighted Beta coefficients so that they sum up to 100%.

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@R_Graph_Gallery @JoachimSchork I find {ggdist} very useful to visualize distributions, e.g stat_halfeye()

https://t.co/NlAhRXeOtm

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@JoachimSchork Are you going to cover the usage of packages from @easystats4u in the course?