Potpourri: Statistics #92

1647. Data Vis Dispatch: January 3, January 10, January 17, January 24, January 311648. The list of 2022 visualization lists1649. From Documents to Data: A Framework for Total Corpus Quality1650. Efficient Python for Data Scientists1651. Deep R Programming1652. Minimalist Data Wrangling with Python1653. Everything You Wanted to Know about the Kernel Trick (But Were Too Afraid to Ask)1654. fastStat: All of REAL Statistics1655. Big, Open and Linked Data: Effects and Value for the Economy1656. Introducing geom_terrorbar()1657. A public repository of personal ML/DS blogs1658. simple-data-analysis.js: Easy-to-use JavaScript library for most common data analysis tasks1659. Quantile Regression as an useful Alternative for Ordinary Linear Regression1660. Winners of the 2022 Table Contest1661. Combining plots in ggplot21662. Prediction Modeling with the Cox model - all about the baseline hazard1663. Multiple Regression using caret1664. MLOps: The Whole Game1665. An intro to dplyr::across1666. Probabilistic Machine Learning: Advanced Topics1667. Annotated History of Modern AI and Deep Learning1668. A list of open geospatial datasets available on AWS, Earth Engine, Planetary Computer, NASA CMR, and STAC Index1669. Introduction to Graph Machine Learning1670. A Succinct Summary of Reinforcement Learning1671. Combining R and Python with {reticulate} and Quarto1672. A Guide To Getting Data Visualization Right1673. Level Up Your Python1674. Exploratory spatial data analysis with Python1675. 6 tips for creating charts for social media1676. balance: a python package for balancing biased data samples1677. A Guide to Analyzing Large N, Large T Panel Data1678. On Moving from Statistics to Machine Learning, the Final Stage of Grief1679. SQL and noSQL approaches to creating & querying databases (using R)1680. The Illustrated Machine Learning website1681. An overview of parsing algorithms1682. Introduction to data structures and algorithms1683. Understanding Deep Learning1684. AI4PH: Text Analyses with R1685. Easily re-using self-written functions: the power of gist + code snippet duo1686. The Bitter Lesson1687. Logistic regression is not fucked1688. These Are Not the Effects You Are Looking For: The Fallacy of Mutual Adjustment and How to Avoid It1689. Discovering the best Chess960 variation1690. ggplot tricks1691. Alone R package: Datasets from the survival TV series1692. Geospatial distributed processing with furrr1693. Visualising the 2022 Australian federal election with geom_sugarbag1694. Time series resources1695. Notes on Hainmueller, Mummolo & Xu: How Much Should we Trust Estimates from Multiplicative Interaction Models?1696. Equivalence testing for linear regression1697. Simpson's Paradox and Existential Terror1698. Recreating a chart from history: a beginner’s look in the data vis world1699. Improving the responsiveness of Shiny applications1700. Telling Stories with Data: With applications in R1701. ggpathway: A tutorial for pathway visualization using tidyverse, igraph, and ggraph1702. Pandas Illustrated: The Definitive Visual Guide to Pandas1703. Much Ado About Sampling1704. My journey from R to Julia1705. Never Test for Normality1706. Foundations of Data Science1707. Course Materials for Advanced Data Analytics in Economics1708. 6 easy ways to map population density in R1709. Mathematical Logic through Python

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