Aneesh Sathe<p><strong>My Road to Bayesian Stats</strong></p><p class="">By 2015, I had heard of Bayesian Stats but didn’t bother to go deeper into it. After all, significance stars, and p-values worked fine. I started to explore Bayesian Statistics when considering small sample sizes in biological experiments. How much can you say when you are comparing means of 6 or even 60 observations? This is the nature work at the edge of knowledge. Not knowing what to expect is normal. Multiple possible routes to a seen a result is normal. Not knowing how to pick the route to the observed result is also normal. Yet, our statistics fails to capture this reality and the associated uncertainties. There must be a way I thought. </p><a href="https://aneeshsathe.com/wp-content/uploads/2025/07/image-from-rawpixel-id-2968487-jpeg.jpg" rel="nofollow noopener" target="_blank"></a>Free Curve to the Point: Accompanying Sound of Geometric Curves (1925) print in high resolution by Wassily Kandinsky. Original from The MET Museum. Digitally enhanced by rawpixel.<p>I started by searching for ways to overcome small sample sizes. There are minimum sample sizes recommended for t-tests. Thirty is an often quoted number with qualifiers. Bayesian stats does not have a minimum sample size. This had me intrigued. Surely, this can’t be a thing. But it is. Bayesian stats creates a mathematical model using your observations and then samples from that model to make comparisons. If you have any exposure to AI, you can think of this <em>a bit</em> like training an AI model. Of course the more data you have the better the model can be. But even with a little data we can make progress. </p><p>How do you say, there is something happening and it’s interesting, but we are only x% sure. Frequentist stats have no way through. All I knew was to apply the t-test and if there are “***” in the plot, I’m golden. That isn’t accurate though. Low p-values indicate the strength of evidence against the null hypothesis. Let’s take a minute to unpack that. The null hypothesis is that nothing is happening. If you have a control set and do a treatment on the other set, the null hypothesis says that there is no difference. So, a low p-value says that it is unlikely that the null hypothesis is true. But that does not imply that the alternative hypothesis <em>is</em> true. What’s worse is that there is no way for us to say that the control and experiment have no difference. We can’t accept the null hypothesis using p-values either. </p><p>Guess what? Bayes stats can do all those things. It can measure differences, accept and reject both null and alternative hypotheses, even communicate how uncertain we are (more on this later). All without making assumptions about our data.</p><p>It’s often overlooked, but frequentist analysis also requires the data to have certain properties like normality and equal variance. Biological processes have complex behavior and, unless observed, assuming normality and equal variance is perilous. The danger only goes up with small sample sizes. Again, Bayes requires you to make no assumptions about your data. Whatever shape the distribution is, so called outliers and all, it all goes into the model. Small sample sets do produce weaker fits, but this is kept transparent. </p><p>Transparency is one of the key strengths of Bayesian stats. It requires you to work a little bit harder on two fronts though. First you have to think about your data generating process (DGP). This means how do the data points you observe came to be. As we said, the process is often unknown. We have at best some guesses of how this could happen. Thankfully, we have a nice way to represent this. DAGs, directed acyclic graphs, are a fancy name for a simple diagram showing what affects what. Most of the time we are trying to discover the DAG, ie the pathway of a biological outcome. Even if you don’t do Bayesian stats, using DAGs to lay out your thoughts is a great. In Bayesian stats the DAGs can be used to test if your model fits the data we observe. If the DAG captures the data generating process the fit is good, and not if it doesn’t. </p><p>The other hard bit is doing analysis and communicating the results. Bayesian stats forces you to be verbose about your assumptions in your model. This part is almost magicked away in t-tests. Frequentist stats also makes assumptions about the model that your data is assumed to follow. It all happens so quickly that there isn’t even a second to think about it. You put in your data, click t-test and woosh! You see stars. In Bayesian stats stating the assumptions you make in your model (using DAGs and hypothesis about DGPs) communicates to the world what and why you think this phenomenon occurs. </p><p>Discovering causality is the whole reason for doing science. Knowing the causality allows us to intervene in the forms of treatments and drugs. But if my tools don’t allow me to be transparent and worse if they block people from correcting me, why bother?</p><p>Richard McElreath says it best:</p><blockquote><p>There is no method for making causal models other than science. There is no method to science other than honest anarchy.</p></blockquote><p><a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/ai/" target="_blank">#AI</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/bayesian-statistics/" target="_blank">#BayesianStatistics</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/biological-data-analysis/" target="_blank">#BiologicalDataAnalysis</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/business/" target="_blank">#Business</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/causal-inference-2/" target="_blank">#CausalInference</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/dags/" target="_blank">#DAGs</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/data-generating-process/" target="_blank">#DataGeneratingProcess</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/data-science/" target="_blank">#dataScience</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/experimental-design/" target="_blank">#ExperimentalDesign</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/frequentist-vs-bayesian/" target="_blank">#FrequentistVsBayesian</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/leadership/" target="_blank">#Leadership</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/machine-learning/" target="_blank">#machineLearning</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/philosophy/" target="_blank">#philosophy</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/science/" target="_blank">#science</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/scientific-method/" target="_blank">#ScientificMethod</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/small-sample-size/" target="_blank">#SmallSampleSize</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/statistical-modeling/" target="_blank">#StatisticalModeling</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/statistical-philosophy/" target="_blank">#StatisticalPhilosophy</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/statistics/" target="_blank">#statistics</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/transparent-science/" target="_blank">#TransparentScience</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/uncertainty-quantification/" target="_blank">#UncertaintyQuantification</a></p>
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Cindy<p>Are you outraged by <a href="https://mastodon.social/tags/RFK" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RFK</span></a> 's oversight over YOUR health, YOUR well being & YOUR life?</p><p>Review this👇 petition & Sign✍ joining me, to have him resign from his position<br><a href="https://www.change.org/p/stand-with-the-cdc-demand-robert-f-kennedy-jr-s-resignation-now" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">change.org/p/stand-with-the-cd</span><span class="invisible">c-demand-robert-f-kennedy-jr-s-resignation-now</span></a></p><p><a href="https://mastodon.social/tags/CDC" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CDC</span></a> <a href="https://mastodon.social/tags/vaccinations" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vaccinations</span></a> <a href="https://mastodon.social/tags/vaccines" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vaccines</span></a> <a href="https://mastodon.social/tags/Covid" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Covid</span></a> <a href="https://mastodon.social/tags/CovidVaccine" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CovidVaccine</span></a> <a href="https://mastodon.social/tags/PublicHealth" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PublicHealth</span></a> <a href="https://mastodon.social/tags/SCIENCE" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SCIENCE</span></a> <a href="https://mastodon.social/tags/ScientificResearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ScientificResearch</span></a> <a href="https://mastodon.social/tags/ScientificMethod" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ScientificMethod</span></a> <a href="https://mastodon.social/tags/ScientificEvidence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ScientificEvidence</span></a> <a href="https://mastodon.social/tags/ScientificPublications" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ScientificPublications</span></a> <a href="https://mastodon.social/tags/Scientists" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Scientists</span></a></p>
Michael Vera<p>I'm claiming Unification, not Perfection:</p><p><a href="https://www.michaelvera.org/Unified_Theory_of_Energy.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">michaelvera.org/Unified_Theory</span><span class="invisible">_of_Energy.html</span></a></p><p><a href="https://mastodon.michaelvera.org/tags/physics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>physics</span></a> <a href="https://mastodon.michaelvera.org/tags/theoreticalphysics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>theoreticalphysics</span></a> <a href="https://mastodon.michaelvera.org/tags/unifiedtheory" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>unifiedtheory</span></a> <a href="https://mastodon.michaelvera.org/tags/energy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>energy</span></a> <a href="https://mastodon.michaelvera.org/tags/science" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>science</span></a> <a href="https://mastodon.michaelvera.org/tags/quantumphysics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>quantumphysics</span></a> <a href="https://mastodon.michaelvera.org/tags/relativity" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>relativity</span></a> <a href="https://mastodon.michaelvera.org/tags/futureofscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>futureofscience</span></a> <a href="https://mastodon.michaelvera.org/tags/einstein" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>einstein</span></a> <a href="https://mastodon.michaelvera.org/tags/newphysics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>newphysics</span></a> <a href="https://mastodon.michaelvera.org/tags/astrophysics" class="mention 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target="_blank">#<span>unification</span></a> <a href="https://mastodon.michaelvera.org/tags/gravitationaltheory" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>gravitationaltheory</span></a> <a href="https://mastodon.michaelvera.org/tags/electromagnetism" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>electromagnetism</span></a> <a href="https://mastodon.michaelvera.org/tags/thermodynamics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>thermodynamics</span></a> <a href="https://mastodon.michaelvera.org/tags/space" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>space</span></a> <a href="https://mastodon.michaelvera.org/tags/time" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>time</span></a> <a href="https://mastodon.michaelvera.org/tags/matter" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>matter</span></a> <a href="https://mastodon.michaelvera.org/tags/sciencematters" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>sciencematters</span></a> <a href="https://mastodon.michaelvera.org/tags/scienceisawesome" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>scienceisawesome</span></a> <a href="https://mastodon.michaelvera.org/tags/nextgenphysics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>nextgenphysics</span></a> <a href="https://mastodon.michaelvera.org/tags/physicslover" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>physicslover</span></a> <a href="https://mastodon.michaelvera.org/tags/physicscommunity" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>physicscommunity</span></a> <a href="https://mastodon.michaelvera.org/tags/energytheory" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>energytheory</span></a> <a href="https://mastodon.michaelvera.org/tags/unified" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>unified</span></a></p>
𝗖 𝗔 𝗧<p><span class="h-card" translate="no"><a href="https://mastodon.social/@silentexception" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>silentexception</span></a></span> </p><p>Science is nothing like religion. Science is a method that uses evidence and peer-review processes to verify the validity of its claims. Religion is the opposite. It has dictates by a god that are to be accepted implicitly and not questioned, even if they make no sense logically or scientifically.</p><p><a href="https://mastodon.social/tags/science" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>science</span></a> <a href="https://mastodon.social/tags/religion" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>religion</span></a> <a href="https://mastodon.social/tags/god" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>god</span></a> <a href="https://mastodon.social/tags/scientificmethod" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>scientificmethod</span></a></p>
Miguel Afonso Caetano<p>"A regulation that works might well produce no visible sign that it's working. If your water purification system works, everything is fine. It's only when you get rid of the sanitation system that you discover why it was there in the first place, a realization that might well arrive as you expire in a slick of watery stool with a rectum so prolapsed the survivors can use it as a handle when they drag your corpse to the mass burial pits.</p><p>When Musk and Ramaswamy decry the influence of "unelected bureaucrats" on your life as "undemocratic," they sound reasonable. If unelected bureaucrats were permitted to set policy without democratic instruction or oversight, that would be autocracy.</p><p>Indeed, it would resemble life on the Tesla factory floor: that most autocratic of institutions, where you are at the mercy of the unelected and unqualified CEO of Tesla, who holds the purely ceremonial title of "Chief Engineer" and who paid the company's true founders to falsely describe him as its founder.</p><p>But that's not how it works! At its best, expert regulations turns political choices in to policy that reflects the will of democratically accountable, elected representatives. Sometimes this fails, and when it does, the answer is to fix the system – not abolish it."</p><p><a href="https://pluralistic.net/2024/11/21/policy-based-evidence/#decisions-decisions" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">pluralistic.net/2024/11/21/pol</span><span class="invisible">icy-based-evidence/#decisions-decisions</span></a></p><p><a href="https://tldr.nettime.org/tags/Science" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Science</span></a> <a href="https://tldr.nettime.org/tags/ScientificMethod" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ScientificMethod</span></a> <a href="https://tldr.nettime.org/tags/Regulation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Regulation</span></a> <a href="https://tldr.nettime.org/tags/AntiScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AntiScience</span></a> <a href="https://tldr.nettime.org/tags/Libertarianism" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Libertarianism</span></a></p>
Coach Pāṇini ®<p><span class="h-card" translate="no"><a href="https://mastodon.social/@RVLara23" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>RVLara23</span></a></span> <br>It’s just the <a href="https://mastodon.world/tags/ScientificMethod" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ScientificMethod</span></a> 🤷🏻♂️</p>
Coach Pāṇini ®<p><span class="h-card" translate="no"><a href="https://zeroes.ca/@hannu_ikonen" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>hannu_ikonen</span></a></span> <br>The official name of <a href="https://mastodon.world/tags/FAFO" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAFO</span></a> is the <a href="https://mastodon.world/tags/ScientificMethod" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ScientificMethod</span></a>:</p>
Church of Jeff<p><a href="https://mastodon.world/tags/science" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>science</span></a> <a href="https://mastodon.world/tags/scientificmethod" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>scientificmethod</span></a></p>
ma𝕏pool<p>The piranha problem: Large effects swimming in a small pond.<br>Christopher Tosh, Philip Greengard, Ben Goodrich, Andrew Gelman, <span class="h-card" translate="no"><a href="https://bayes.club/@avehtari" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>avehtari</span></a></span>, <span class="h-card" translate="no"><a href="https://mathstodon.xyz/@djhsu" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>djhsu</span></a></span> <br>2 Apr 2024<br> <a href="https://arxiv.org/abs/2105.13445" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">arxiv.org/abs/2105.13445</span><span class="invisible"></span></a></p><p>In a lot of social science research, small, random factors are reported as having large effects on social and political attitudes and behavior (social priming, hormonal levels,parental socioeconomic status, weather, ...). Studies have claimed to find large effects from these and other inputs.</p><p>The results show that it would be extremely unlikely to have all these large effects coexisting—they would have to almost exactly cancel each other out.</p><p><a href="https://mathstodon.xyz/tags/socialScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>socialScience</span></a> <a href="https://mathstodon.xyz/tags/replicationCrisis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>replicationCrisis</span></a> <a href="https://mathstodon.xyz/tags/statistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statistics</span></a> <a href="https://mathstodon.xyz/tags/quantitative" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>quantitative</span></a> <a href="https://mathstodon.xyz/tags/research" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>research</span></a> <a href="https://mathstodon.xyz/tags/science" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>science</span></a> <a href="https://mathstodon.xyz/tags/scientificMethod" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>scientificMethod</span></a></p>
Violet<p>Here's another article based on a trend I just don't get. Studies that yield negative results tend not to be published, or even submitted for publication. The article refers to such studies several times as "failed" studies. </p><p>This runs contrary to the principle I taught my junior high science students thirty years ago. I had them come up with an experimental design, create a hypothesis, perform the experiment, and document their results, just like any science class. The most significant lesson from this process isn't just how to perform and document an experiment; it's recognizing that even if your hypothesis is incorrect, you've learned something about the phenomenon you're studying. </p><p>It's hard to believe that the scientific community overall is just realizing the importance of negative or unexpected results. The next time someone studies a certain phenomenon, reviewing negative results tells them what to exclude or control. Otherwise they may unknowingly include factors that have already been shown to affect the results. </p><p><a href="https://lgbtqia.space/tags/Science" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Science</span></a> <a href="https://lgbtqia.space/tags/ScientificMethod" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ScientificMethod</span></a> <a href="https://lgbtqia.space/tags/Methodology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Methodology</span></a> </p><p><a href="https://www.nature.com/articles/d41586-024-01389-7" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">nature.com/articles/d41586-024</span><span class="invisible">-01389-7</span></a></p>
Andy Baker<p>Earth and Environmental Science – week 8</p><p>It is week 8 in the UNSW Earth and Environmental Science course, and the class is working towards writing a lab report on Sydney soil lead pollution. Last week, students used a portable x-ray fluorescence analyser to test soil samples that they had collected from their homes or across UNSW campus. This week the focus of the class was hypothesis testing.</p><p><a href="https://aus.social/tags/academia" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>academia</span></a> <a href="https://aus.social/tags/teaching" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>teaching</span></a> <a href="https://aus.social/tags/education" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>education</span></a> <a href="https://aus.social/tags/pollution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>pollution</span></a> <a href="https://aus.social/tags/soils" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>soils</span></a> <a href="https://aus.social/tags/environmentalscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>environmentalscience</span></a> <a href="https://aus.social/tags/earthscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>earthscience</span></a> <a href="https://aus.social/tags/science" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>science</span></a> <a href="https://aus.social/tags/scientificmethod" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>scientificmethod</span></a> <a href="https://aus.social/tags/Sydney" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Sydney</span></a> <a href="https://aus.social/tags/UNSW" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>UNSW</span></a> <a href="https://aus.social/tags/GEOS1211" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GEOS1211</span></a></p><p><a href="http://andy-baker.org/2024/04/04/earth-and-environmental-sciences-week-8/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">http://</span><span class="ellipsis">andy-baker.org/2024/04/04/eart</span><span class="invisible">h-and-environmental-sciences-week-8/</span></a></p>
Miguel Afonso Caetano<p><a href="https://tldr.nettime.org/tags/Journalism" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Journalism</span></a> <a href="https://tldr.nettime.org/tags/ScientificJournalism" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ScientificJournalism</span></a> <a href="https://tldr.nettime.org/tags/ScientificMethod" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ScientificMethod</span></a>: "Angwin sees that unraveling as Proof’s job, and she’s looking to science, rather than journalistic traditions, to inform the publication’s work. She wants Proof’s work to be inspired by the scientific method rather than ideas of objectivity: reporters will develop hypotheses and test them through the reporting process, building software and data sets that will be released to the public for review. Much like a published scientific paper, each story will also be accompanied by an “ingredients label” that lays out its hypothesis, sample size, reporting techniques, key findings, and limitations.</p><p>Developing a hypothesis is another term for asking questions, which is essential to all journalism, and in her letter Angwin admits that looking to science is not a new idea; Walter Lippmann, the namesake of the building that houses the Nieman Foundation, called for a scientific approach rather than chasing scoops back in 1922, and Angwin herself wrote about the idea last year.</p><p>Unlike scientists, Proof’s journalists will not be subjected to the processes like IRBs or peer reviews that have become hallmarks of modern-day scientific publishing. “It’s not realistic for journalism to [be subjected to those processes] because we are still trying to be faster than science can usually move,” Angwin said. “I see the scientific method is more of a philosophical approach, something I’m aiming toward but not aiming to achieve.” <a href="https://www.niemanlab.org/2024/03/proof-news-is-julia-angwins-attempt-to-bring-the-scientific-method-to-investigative-journalism/" rel="nofollow noopener" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">niemanlab.org/2024/03/proof-ne</span><span class="invisible">ws-is-julia-angwins-attempt-to-bring-the-scientific-method-to-investigative-journalism/</span></a></p>
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