Small-sample research is everywhere, but the methods actually designed for it? Basically ghosts. 👻📊 We need to learn these methods faster, and the best way is together. What if we treated statistical exploration like citizen science? (Think eBird, but for stats 🦅🔬). In this thread, we use a Replext app from mightymetrika to crowdsource, replicate, and extend a method called "informative hypothesis testing." Let’s dive in! 🧵👇 🌐: mightymetrika.com/citsci 📊: mightymetrika.shinyapps.io/m… #rstats #statistics #math #simulation #citizenscience #science #data 1/

Group averages can lie. 📉 In small-sample longitudinal studies, looking only at the mean can hide the real story. Visualizing individual trajectories reveals hidden heterogeneity, non-linear trends, and critical outliers. Here’s a practical tool from Carrig, Wirth, & Curran (2004; 10.1207/S15328007SEM1101_9) to fix that. 🧵👇 1/ #RStats #Statistics #Math #Simulation #Data #DataScience #MachineLearning #Graphics

P-values can hold your small-sample studies back. 📉 “Not significant” ≠ “No effect.” Bayes factors fix this. They let you weigh the evidence for multiple plausible hypotheses at once—including your theory vs. the null. It’s time to upgrade how we measure evidence. 👇🧵 1/

Hard to collect a large sample size for your #clinical intervention #research? 🧐 Single-Case Experimental Designs (SCEDs) are a powerful alternative! Participants serve as their own controls, measured repeatedly over time [Maric, Marija & Werff, Vera. (2020). Single-Case Experimental Designs in Clinical Intervention Research. 10.4324/9780429273872-9] Note: To meet strict WWC 5.0 standards, a well-designed SCED needs built-in replication (like an ABAB #design), not just a simple A-B phase. [ies.ed.gov/ncee/WWC/Handbook…] But regardless of the specific design, how do we validate that our data shows a meaningful, reliable effect? Enter: The Non-Overlap of All Pairs (NAP). #RStats #Math #Statistics #Programming #ggplot2 #Simulation 🧵👇 1/12

been feeling kinda stressed lately so I made a little prototype is this anything

Does an effect hold for everyone the sample, or just on average? 🤔 Detecting a group-level effect doesn't guarantee it applies to every individual. Klaassen (10.4324/9780429273872-11) proposed a method to evaluate hypotheses case-by-case and aggregate the results. 🧵👇 #RStats

This game dev is making a game where you fly through a semi-open world as a paper plane. Wow! - Transform between a plane, ball, or boat in real-time - Realistic physics - Unlockable upgrades The game is called Paper Sky. Release date TBA.

🔬 Help us better understand statistical methods tailored for smaller datasets by contributing to our citizen science projects. 📊 Submit data: mightymetrika.com/citsci💻 Contribute code & bug reports: github.com/mightymetrika Every contribution counts! 💪 #math #RStats

particle life in 3d controlled by hands 🪸 - adjust spacing of all particles - move any type of particles

Want to build #RStats #CitizenScience tools? 🧑‍💻 At mightymetrika.com, we use mmints to streamline our REPLEXT Shiny apps. It includes PostgreSQL database modules and more. Contribute today: github.com/mightymetrika/mmi… #statistics #data

Ever read a brilliant statistics paper, but realized its simulation parameters don't quite match your real-world project? 🤔 Meet the REPLEXT (Replication & Extension) framework! 🚀 Let's bridge the gap between published research and your actual data. 1/4

a=(x,y,d=mag(k=(5 sin(y))*cos(x*2),e=y/6-13)-3)=>point((q=3*sin(k*2) k/19*y*(e d/3*sin(e-d*4 t)) 99)*sin(c=d-t/4 i%2*8)*cos(c/4 e/3) 200,q*d/9*cos(c/2 7) 200) t=0,draw=$=>{t||createCanvas(w=400,w);background(9).stroke(w,126);for(t =PI/30,i=2e4;i--;)a(i,i/1e3)}#つぶやきProcessing

#ゲーム試作・実験 #Gemini 画面枠を動かしてボールを上下左右にループさせる、ブロック崩し風ゲームを試作してみた。窓から覗いて空間を切り出すような感触が特徴。 跳ね回るボールを眺めて楽しみつつ、ボールの流れをループで制御しフィールドの隅々まで巡らせていく。