Potpourri: Statistics #91

1592. Data Vis Dispatch: January 4, January 11, January 18, January 25, February 1, February 8, February 15, February 22, March 1, March 15, COVID Trackers Special, March 29, April 5, April 12 April 19, April 26, May 3, May 10, May 17, May 24, May 31, June 7, June 14, June 21, June 28, July 5, July 12, July 19, July 26, August 2, August 9, August 16, August 23, September 6, September 20, October 4, October 11, October 18, October 25, November 1, November 8, November 15, November 22, November 29, December 6, December 13, December 20, December 271593. Causal Inference | Hypothesis Testing | All at Once1594. Build a Shiny App Demo1595. Animated population tree maps1596. Type inference in readr and arrow1597. How I learn machine learning1598. Wrangling data in JavaScript with Arquero: a primer for R users1599. How To R: Visualizing Distributions, Making Better Histograms1600. Analyzing All Recipes1601. Philosophy of Statistics1602. Webscraping with RSelenium: Automate your browser actions1603. Generalized Visual Language Models1604. Open source is a hard requirement for reproducibility1606. Reproducibility with Docker and Github Actions for the average R enjoyer1606. Learning Excel as an R user1607. Analyzing Projected Calculations Using R1608. Bar plot checklist1609. Panel Data (DiD, Synth, MC) Causal Inference1610. A Visual Bibliography of Tree Visualization 2.01611. I’m not a real statistician, and you can be one too1612. R package reviews {gtsummary} Publication-Ready Tables of Data, Stat-Tests and Models!1613. Understanding The Harmonic Mean1614. Some notes about improving base R code1615. Model Calibration1616. Monitoring quarto-dev repositories: Creating a workflow with GitHub Actions for R users1617. Automated Tufte-style weather graphs1618. Automatically deploying a Shiny app for browsing #RStats tweets with GitHub Actions1619. Weird & wonderful: Hungarian data graphics1620. Building a ggplot2 rollercoaster: Creating amazing 3D data visualizations in R1621. The WorldStrat dataset1622. NormConf: Lightning Talks1623. Which R packages do scientists use?1624. Read and Visualize your Twitter Archive1625. Practical Deep Learning for Coders1626. How to use natural and base 10 log scales in ggplot21627. Hillshade, colors and marginal plots with tidyterra: I: How to overlay SpatRasters, II: The rain in Spain does not stay mainly in the plain1628. NLP Demystified1629. On Probability versus Likelihood1630. ChatGPT Resources1631. High-Dimensional Probability and Applicaitons in Data Science1632. Introducing the googletraffic R Package: A new tool to measure congestion across large spatial areas1633. Historical analogies for large language models1634. Extended Two-way Fixed Effects (ETWFE)1635. How The Economist makes the best charts on the internet1636. Random Forests for Complete Beginners1637. Terrorism and Counterterrorism Datasets: An Overview1638. Scaling down Deep Learning1639. Annotated Forest Plots using ggplot21640. Applied Causal Analysis (with R)1641. Simpson's paradox all the way down1642. Data Science in Julia for Hackers1643. R packages for visualising spatial data1644. [A Short Guide for Feature Engineering and Feature Selection](https://github.com/Yimeng-Zhang/feature-engineering-and-feature-selection/blob/master/A Short Guide for Feature Engineering and Feature Selection.md)1645. Modeling Key World Cup Moments with Machine Learning1646. The Turing Way

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