Comments for Katie Howgate /stor-i-student-sites/katie-howgate STOR-i PhD Student Tue, 25 Jul 2023 03:44:35 +0000 hourly 1 https://wordpress.org/?v=6.9.4 Comment on Hypergraphs – not just a cool name! by Expanders make very non-intuitive hypergraphs – cubetown /stor-i-student-sites/katie-howgate/2021/04/29/hypergraphs-not-just-a-cool-name/#comment-245 Tue, 25 Jul 2023 03:44:35 +0000 /stor-i-student-sites/katie-howgate/?p=746#comment-245 […] begin with a definition. A hypergraph is a set of vertices and edge set . Here is a great blog post introducing the basics of hypergraph structure, as well as some of their […]

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Comment on Fraud in the 2020 US Election?!?! by Benford’s Law and Trump vs. Biden 2020 Chicago results – Matthew van Eerde's web log /stor-i-student-sites/katie-howgate/2021/03/12/fraud-in-the-2020-us-election/#comment-25 Fri, 20 May 2022 18:28:53 +0000 /stor-i-student-sites/katie-howgate/?p=620#comment-25 […] Image credit: Katie Howgate […]

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Comment on A Bayesian Approach To Finding Lost Objects by JP /stor-i-student-sites/katie-howgate/2021/02/08/a-bayesian-approach-to-finding-lost-objects/#comment-6 Wed, 15 Sep 2021 11:47:32 +0000 http://www.lancaster.ac.uk/stor-i-student-sites/katie-howgate/?p=377#comment-6 Hi Katie,
Excellent, clear explanation by stripping it right down to the core!

One thing I noticed is that the in the initial “Probability density map for where I dropped my phone (based on my knowledge of where I dropped” grid the sum of probabilities equates to 1, but in the “Revised probability that my phone is in a certain square.” it does not (0.93)

Shouldn’t this not always sum up to 1?

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Comment on A Bayesian Approach To Finding Lost Objects by Wieslaw /stor-i-student-sites/katie-howgate/2021/02/08/a-bayesian-approach-to-finding-lost-objects/#comment-3 Thu, 24 Jun 2021 07:18:03 +0000 http://www.lancaster.ac.uk/stor-i-student-sites/katie-howgate/?p=377#comment-3 just few things which are not clear for me:
– for clarity you could add explicitly P(Not found | Is not there) to Bayes formula and say that it is 1 (hard to find something if it isn’t there)
– also you could say that P(Not found | Is there) + P(Found | Is there) = 1
but for me the last formula is somewhat foggy. Could you give an example of computation here please?

Anyway, cool blog

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