Statistical Methods and Data Analytics
While machine learning methods have traditionally been used for prediction in fields like industry and technology, they are increasingly being adopted in scientific research for exploration and inference. This two-part workshop introduces key machine learning techniques used for scientific applications. Part 1 discusses core concepts such as prediction accuracy, the bias-variance tradeoff, and cross-validation. Part...
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While machine learning methods have traditionally been used for prediction in fields like industry and technology, they are increasingly being adopted in scientific research for exploration and inference. This two-part workshop introduces key machine learning techniques used for scientific applications. Part 1 discusses core concepts such as prediction accuracy, the bias-variance tradeoff, and cross-validation. Part...
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This workshop will show how descriptive analyses, both numerical and graphical, can be done with continuous and categorical variables. Subpopulation analysis will be discussed, and then examples of OLS regression and logistic regression will be considered. The workshop notes will be posted soon. Register here: https://ucla.zoom.us/meeting/register/IJ-3bjGqS5i6CANjV4fcbg#/registration
This workshop will cover both the use of descriptive and inferential statistics with complex survey data in SAS. We will also discuss regression commands, the analysis of subpopulations, and some graphical methods that can be used with weighted data. The workshop notes are here. Register here: https://ucla.zoom.us/meeting/register/knDT7SbKRDSWFuyqeAsMzQ#/registration
R is a powerful programming language specifically designed for statistical analysis. In this workshop, we will explore some of the tools and packages available in R to craft visually appealing tables that effectively communicate your results. Whether you’re using R Markdown and seeking to generate tables in your HTML file or aiming to create polished...
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Choosing which covariates to control for in regression models is a well-known challenge, and clear guidance on this issue is often lacking. Causal diagrams, specifically directed acyclic graphs (DAGs), offer a powerful framework for addressing this challenge. This workshop discusses the paper “A Crash Course in Good and Bad Controls” (Cinelli, Forney, & Pearl, 2022), which...
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