How do you choose between bootstrap confidence intervals, randomization tests, and the two-sample t-test—and defend that choice in your research? Join Ken Gerow for an Instats online seminar designed for PhD students and professional researchers who want to strengthen their statistical reasoning, not just expand their analytical toolkit. Explore how resampling and permutation methods differ, when to use them for estimation or hypothesis testing, and why assumptions about equal and unequal variances matter. With applications across biological, ecological, clinical, and other scientific data, this seminar will help you make principled methodological choices and communicate more defensible statistical claims in theses, manuscripts, and collaborative research. Attend live via Zoom or revisit the recordings and materials for 30 days afterward, with access to an expert-monitored Q&A forum during that period. An official Instats certificate of completion is included. #Biology #Biostatistics #Botany #ClinicalorLaboratoryScience #Ecology #EnvironmentalSciences #FisheriesBiology #LifeSciences #Microbiology #NaturalSciences #Simulation #Statistics #Zoology #Research #ResearchTraining #Instats

How can researchers use large language models without compromising causal rigor? Join our online seminar on Causal Inference and Large Language Models, designed for PhD students, postdoctoral researchers, and academic staff working with textual, social media, administrative, or mixed-format data. Taught by Moses Boudourides (Northwestern University), this seminar explores how LLMs can be integrated into causal inference workflows to measure latent constructs, generate candidate instruments, support causal discovery, estimate treatment effects with high-dimensional text data, and audit bias in LLM-derived variables. Participants will engage with conceptual foundations and applied workflows using reproducible, fully annotated Python and R scripts, diagnostic tools, and publication-oriented strategies. No prior knowledge of causal inference, LLMs, programming, or coding is required; general familiarity with quantitative research is sufficient. The seminar is delivered online via Zoom, with recordings, slides, scripts, data, readings, and a monitored Q&A forum available for 30 days after the seminar. Participants receive an official Instats certificate of completion, with ECTS Equivalent points where applicable. #AppliedResearch #BayesianStatistics #CausalInference #ComputationalSocialScience #ComputationalStatistics #ComputerScience #DataScience #Economics #EnvironmentalSciences #Finance #Healthcare #MachineLearning #Management #MixedMethods #OrganizationStudies #RegressionModelingStrategies #ResearchMethods #SocialSciences #Sociology #Statisticalmodellingandregression #Statistics #SocialTheory #Python #R #Research #ResearchTraining #Instats

Ready to strengthen your statistical toolkit and make better use of data that varies across both time and entities? Join our online workshop, Using ChatGPT with Stata: Panel Data Analysis, designed for PhD students and professional researchers who want practical, hands-on experience with panel data methods in Stata. This seminar will guide you through key approaches including pooled OLS, fixed effects, random effects, between-effects models, first-difference models, time-series cross-section methods, binary temporal models, and dynamic panel models such as Arellano-Bond using xtabond2. A distinctive feature of the workshop is the integration of ChatGPT as a learning assistant to help clarify concepts, generate and refine Stata commands, explore modeling choices, and support troubleshooting during applied lab sessions. Participants should be familiar with basic regression and descriptive statistics, but no prior panel data experience is required. By the end of the course, you will be better equipped to identify panel data structures, choose appropriate modeling strategies, implement them in Stata, and interpret results with confidence. #Business #Economics #EnvironmentalSciences #Finance #PoliticalScience #PublicHealth #Sociology #Statistics #Econometrics #DataScience #Stata #Research #ResearchTraining #Instats

Air pollution is a major environmental health challenge, but estimating its true effects on mortality and morbidity is far from straightforward. In this online seminar for PhD students and professional researchers, Michael Cork, MPH, PhD Candidate at the Harvard T.H. Chan School of Public Health, will provide an accessible and policy-relevant overview of statistical methods for estimating how pollution impacts health, with a focus on exposure–response curves and how different methodological choices can shape conclusions about “safe” pollution levels. The seminar will introduce key ideas from causal inference, including confounding, exchangeability, and weighting, and compare them with traditional regression-based approaches, drawing on recent JRSS-A research, simulation evidence, and real-world air-pollution analyses including Medicare-based studies. Although the examples focus on air pollution, the concepts apply broadly to continuous environmental exposures such as temperature, noise, and chemical pollutants. Participants will gain practical insight into nonlinearity, bias, uncertainty, model diagnostics, visualization strategies, and the policy implications of exposure–response estimation. The seminar is offered via Zoom, with recordings and materials available for 30 days, and includes an official Instats certificate of completion. #Biostatistics #DataScience #EnvironmentalSciences #PublicPolicy #Statistics #Epidemiology #PublicHealth #RStudio #R #Research #ResearchTraining #Instats

Join our upcoming online seminar designed for PhD students and professional researchers looking to strengthen their skills in ecological and environmental data analysis. Led by Dr. Oliver Miler from the Northwest Indian Fisheries Commission in Washington State, USA, this workshop introduces participants to multivariate analysis of biotic communities using R, with a focus on understanding complex ecological datasets and their relationships with environmental variables. Topics include core multivariate concepts, applications in ecological research, data preprocessing and management, visualization strategies, and practical sessions using real-world datasets. Delivered via Zoom, the seminar includes access to recordings, slides, code, outputs, and data for 30 days after the course, along with a monitored Q&A forum where participants can continue asking questions. Participants will receive an official Instats certificate of completion, with ECTS Equivalent points available where applicable. #Oceanography #Ecology #Zoology #EnvironmentalSciences #FisheriesBiology #Limnology #MarineBiology #PlantEcology #Biostatistics #Statistics #DataScience #Biology #R #RStudio #Research #ResearchTraining #Instats

Ready to strengthen your quantitative research toolkit? Join our online workshop, Using ChatGPT with Stata: Panel Data Analysis, designed for PhD students and professional researchers who want to analyze data across both time and entities, such as individuals, firms, or countries. This hands-on seminar will guide you through key panel data methods, including pooled OLS, fixed effects, random effects, first-difference models, time-series cross-section approaches, binary panel models, and dynamic panel models using the Arellano-Bond estimator and xtabond2 in Stata. A unique feature of the workshop is the integration of ChatGPT as a learning assistant, helping participants clarify concepts, generate and refine Stata commands, troubleshoot analyses, and explore alternative modeling strategies. No prior experience with panel data is required, but familiarity with basic regression and descriptive statistics is recommended. By the end of the course, you will be better equipped to identify panel data structures, choose appropriate models, implement them in Stata, and interpret your results with confidence. #Business #Economics #EnvironmentalSciences #Finance #PoliticalScience #PublicHealth #Sociology #Statistics #Econometrics #DataScience #Stata #Research #ResearchTraining #Instats

Join our online seminar on Web Scraping in Python for scholarly research, designed for PhD students and professional researchers who want to turn web-based information into structured, analysis-ready data. Led by Kimberly Fessel of Dr Kim Data, this practical workshop covers HTML, the DOM, browser developer tools, requests, BeautifulSoup, reproducible scraping pipelines, data cleaning, JavaScript-rendered pages, Playwright, rate limiting, robots.txt, and responsible data collection practices. Participants will learn how to extract text, links, tables, and other research-relevant content across multiple web pages, while also developing the methodological judgement needed to decide when scraping, APIs, or downloadable datasets are the best choice. Suitable for researchers across the social sciences, public health, environmental studies, digital humanities, media, and computational fields, the seminar includes Zoom livestream access, 30-day access to recordings and materials, a monitored Q&A forum, and an official Instats certificate of completion. #AppliedResearch #Biology #Business #ComputationalSocialScience #DataAnalytics #DataScience #DataScraping #DigitalHumanities #EnvironmentalSciences #Media #PoliticalScience #PublicHealth #Real-WorldData #SocialMedia #SocialSciences #Statistics #InformationScience #ComputerScience #Python #Research #ResearchTraining #Instats