Potpourri: Statistics #66

697. How To Read 2020 Polls Like A Pro698. Visualizing Complex Science 699. What is machine learning, and how does it work?700. Choosing Fonts for Your Data Visualization701. Why linear mixed-effects models are probably not the solution to your missing data problems702. Outstanding User Interfaces with Shiny703. How I Taught Tidymodels, Virtually704. How your colorblind and colorweak readers see your colors705. Graphic Content: How Visualizing Data Is a Life-or-Death Matter706. How to Create Brand Colors for Data Visualization Style Guidelines707. The R package workflow708. Introducing Modeltime: Tidy Time Series Forecasting using Tidymodels709. Tidy Geospatial Networks in R710. PCA with Age of Empires II data711. A practical guide to geospatial interpolation with R712. Oh my GOSH: Calculating all possible meta-analysis study combinations713. Rating children's books with empirical Bayes estimation714. Normalizing and rescaling children's book ratings715. Tips from an R Journalist716. How to improve your R package717. A very short introduction to Tidyverse718. purrr: Introduction and Application719. Supervised Machine Learning for Text Analysis in R720. 4 Tips to Make Your Shiny Dashboard Faster721. How I share knowledge around R Markdown722. Teaching Statistics and Data Science Online723. a ggplot2 grammar guide724. Five Tidyverse Tricks You May Not Know About725. How to build a Tufte-style weather graph in R using ggplot2