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#bayes

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Sarfraaz Ahmed<p>📉Latest MyVoD:-&gt; Don't use GenAI?<br>💡 Visually understanding Bayes' Theorem<br>✨ Python's Performace Anti-Patterns<br>✨ Python's Dictionary Dispatch Pattern</p><p>Latest My Voyage of Discovery: <a href="http://eepurl.com/jcLqOg" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">http://</span><span class="">eepurl.com/jcLqOg</span><span class="invisible"></span></a></p><p>Subscribe for more at: <a href="http://eepurl.com/iu6PFU" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">http://</span><span class="">eepurl.com/iu6PFU</span><span class="invisible"></span></a></p><p><a href="https://mastodon.social/tags/MyVoD" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MyVoD</span></a> <a href="https://mastodon.social/tags/GenAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GenAI</span></a> <a href="https://mastodon.social/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>python</span></a> <a href="https://mastodon.social/tags/Dictionary" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Dictionary</span></a> <a href="https://mastodon.social/tags/Bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Bayes</span></a> <a href="https://mastodon.social/tags/3Blue1Brown" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>3Blue1Brown</span></a> <a href="https://mastodon.social/tags/Pattern" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Pattern</span></a></p>
Ritesh Bhagwat<p>My Ram Navami Greetings with a Bayesian Twist !</p><p><a href="https://mastodon.social/tags/ramnavami" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ramnavami</span></a> <a href="https://mastodon.social/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://mastodon.social/tags/datascience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>datascience</span></a></p>
pglpm<p><span class="h-card" translate="no"><a href="https://lgbtqia.space/@AeonCypher" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>AeonCypher</span></a></span> <span class="h-card" translate="no"><a href="https://mastodon.world/@paninid" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>paninid</span></a></span> </p><p>"A p-value is an <a href="https://c.im/tags/estimate" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>estimate</span></a> of p(Data | Null Hypothesis). " – not correct. A p-value is an estimate of</p><p>p(Data or other imagined data | Null Hypothesis)</p><p>so not even just of the actual data you have. Which is why p-values depend on your stopping rule (and do not satisfy the "likelihood principle"). In this regard, see Jeffreys's quote below.</p><p>Imagine you design an experiment this way: "I'll test 10 subjects, and in the meantime I apply for a grant. At the time the 10th subject is tested, I'll know my application's outcome. If the outcome is positive, I'll test 10 more subjects; if it isn't, I'll stop". Not an unrealistic situation.</p><p>With this stopping rule, your p-value will depend on the probability that you get the grant. This is not a joke.</p><p>"*What the use of P implies, therefore, is that a hypothesis that may be true may be rejected because it has not predicted observable results that have not occurred.* This seems a remarkable procedure. On the face of it the fact that such results have not occurred might more reasonably be taken as evidence for the law, not against it." – H. Jeffreys, "Theory of Probability" §&nbsp;VII.7.2 (emphasis in the original) &lt;<a href="https://doi.org/10.1093/oso/9780198503682.001.0001" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.1093/oso/9780198503</span><span class="invisible">682.001.0001</span></a>&gt;.</p><p><a href="https://c.im/tags/bayesian" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayesian</span></a> <a href="https://c.im/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://c.im/tags/statistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statistics</span></a></p>
Daniel Lakeland<p><a href="https://mastodon.sdf.org/tags/introduction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>introduction</span></a> when the database crashed I lost some followers, but because I hadn't backed up my account yet, I am not sure who they all are. As an extended introduction I'll tag some common topics I like to discuss, maybe people will see those.<br><a href="https://mastodon.sdf.org/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://mastodon.sdf.org/tags/bayesian" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayesian</span></a> <a href="https://mastodon.sdf.org/tags/statistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statistics</span></a> <a href="https://mastodon.sdf.org/tags/appliedmathematics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>appliedmathematics</span></a> <a href="https://mastodon.sdf.org/tags/ipv6" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ipv6</span></a> <a href="https://mastodon.sdf.org/tags/bufferbloat" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bufferbloat</span></a> <a href="https://mastodon.sdf.org/tags/quarto" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>quarto</span></a> <a href="https://mastodon.sdf.org/tags/openscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>openscience</span></a> <a href="https://mastodon.sdf.org/tags/agentbasedmodels" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>agentbasedmodels</span></a> <a href="https://mastodon.sdf.org/tags/julialang" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>julialang</span></a> <a href="https://mastodon.sdf.org/tags/economics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>economics</span></a> <a href="https://mastodon.sdf.org/tags/biology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>biology</span></a> <a href="https://mastodon.sdf.org/tags/molecularbiology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>molecularbiology</span></a> <a href="https://mastodon.sdf.org/tags/ecology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ecology</span></a> <a href="https://mastodon.sdf.org/tags/forensics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>forensics</span></a> <a href="https://mastodon.sdf.org/tags/engineering" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>engineering</span></a></p>
Ed Merkle<p>New case study exploring likelihood computations (+ approximations) for Bayesian structural equation models with ordinal data, with application to WAIC and friends.</p><p><a href="https://ecmerkle.github.io/cs/ord_ic.html" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">ecmerkle.github.io/cs/ord_ic.h</span><span class="invisible">tml</span></a></p><p><a href="https://mastodon.sdf.org/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://mastodon.sdf.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://mastodon.sdf.org/tags/mcmc" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>mcmc</span></a> <a href="https://mastodon.sdf.org/tags/stan" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stan</span></a> <a href="https://mastodon.sdf.org/tags/sem" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>sem</span></a></p>
Emtiyaz Khan<p>Who am I, and why am I here? <a href="https://mastodon.social/tags/introduction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>introduction</span></a></p><p>I am a machine learning researcher, using tools from <a href="https://mastodon.social/tags/Bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Bayes</span></a>, <a href="https://mastodon.social/tags/stats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stats</span></a>, <a href="https://mastodon.social/tags/optimization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>optimization</span></a>, <a href="https://mastodon.social/tags/informationgeometry" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>informationgeometry</span></a>, <a href="https://mastodon.social/tags/deeplearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deeplearning</span></a>, signal processing, etc.</p><p>I care deeply about people, their well-being, inclusion, diversity, equity, privacy, and justice.</p><p>I believe in slow and rigorous scientific process, to add value to existing knowledge, and improve positive impact on society.</p><p>I am here to learn about all of these.</p><p>More about at <a href="https://emtiyaz.github.io/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">emtiyaz.github.io/</span><span class="invisible"></span></a></p>
Daniel Heck<p>Hi! I am an associate professor of Psychological Methods at Philipps-Universität Marburg. </p><p>My <a href="https://mastodon.social/tags/research" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>research</span></a> focuses on cognitive and multinomial modeling, Bayesian statistics, <a href="https://mastodon.social/tags/Bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Bayes</span></a> factors, hierarchical models, meta-analysis, and <a href="https://mastodon.social/tags/psychometrics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>psychometrics</span></a>.</p><p>My personal website is: <a href="https://www.dwheck.de" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="">dwheck.de</span><span class="invisible"></span></a></p>