Potpourri: Statistics #98

1895. Data Vis Dispatch: July 4, July 11, July 18, July 251896. Using a Data Dictionary to Recode Columns with dplyr1897. The ave() Function in R1898. Lessons Learned From Running R in Production1899. Unit Testing Analytics Code1900. A Gentle Introduction to Docker1901. Road trip analysis! How to use and play with Google Location History in R1902. Quantile Loss & Quantile Regression1903. ML system design: 200 case studies to learn from1904. What tokens are used more vs. less in #TidyTuesday place names?1905. Introduction to Statistical Learning with Applications in Python1906. Fumbling my way through an XY problem1907. From forecast to fable, design decisions for statistical software1908. Ordering constraints in brms using contrast coding1909. Tree models for assessing covariate-dependent method agreement1910. Testing functional specification in linear regression1911. CheatSheet for coding in R, Python and Julia1912. Computing the eigendecomposition and the singular value decomposition1913. Demystifying Text Data with the unstructured Python Library (+alternatives)1914. Common methodological mistakes1915. Tips for debugging and cleaning broken code1916. Classification metrics for #TidyTuesday GPT detectors1917. Practical Python Programming1918. Advanced Python Mastery1919. Tidy design principles1920. Making charts that make an impact1921. Why do people use R?1922. Astronomia ex machina: a history, primer and outlook on neural networks in astronomy1923. Comprehensive Python Cheatsheet1924. Emphasize what you want readers to see with color1925. The ultimate practical guide to conjoint analysis with R1926. Supervised Topic Modeling for Short Texts: My Workflow and A Worked Example1927. Jazz up your ggplots!1928. Four reasons to learn HTML + CSS as an R programmer1929. Beyond Item Response Theory: Growth Curve Modeling of Latent Variables with Bayes1930. Large language models, explained with a minimum of math and jargon1931. What is "production" anyway? MLOps for the curious1932. How to fill maps with density gradients with R, {ggplot2}, and {sf}1933. About Tidy Design Principles1934. Predicting a Successful Mt Everest Climb1935. Stat Arb - An Easy Walkthrough1936. Best Practices for Data Visualisation1937. Reducing my for loop usage with purrr::reduce()1938. Adding social media icons to charts with {ggplot2}1939. Annotated equations in ggplot2: Importing latex into ggplot2

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