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Instats

Contact: info@instats.org

Instats is a mission-driven organization devoted to improving research practices across the globe. Instats does this by facilitating expert-led training for PhD and post-PhD researchers across a broad range of fields, methods, and theoretical orientations through the Instats platform.

Instats is seeking partners who share the vision of supporting and improving multidisciplinary research. To do this, individual and institutional partnerships are central to our ethos, and we reflect this in our approach to these partnerships. We work with each partner to offer their content in a way that meets their knowledge community’s interests and needs. Instats helps partners offer their content and expertise by freely providing a full service, technologically sophisticated, easy-to-use platform for delivering seminars and workshops, as well as connecting with the research community more broadly through free community forums, social networking, Q&A boards, and job postings.

Instats https://dresa.org.au/content_providers/instats Instats is a mission-driven organization devoted to improving research practices across the globe. Instats does this by facilitating expert-led training for PhD and post-PhD researchers across a broad range of fields, methods, and theoretical orientations through the Instats platform. Instats is seeking partners who share the vision of supporting and improving multidisciplinary research. To do this, individual and institutional partnerships are central to our ethos, and we reflect this in our approach to these partnerships. We work with each partner to offer their content in a way that meets their knowledge community’s interests and needs. Instats helps partners offer their content and expertise by freely providing a full service, technologically sophisticated, easy-to-use platform for delivering seminars and workshops, as well as connecting with the research community more broadly through free community forums, social networking, Q&A boards, and job postings. /system/content_providers/images/000/000/042/original/instats_logo.jpg?1730854514
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  • Applied Research Methods for Social Scientists with James F. Downes, Center for Research and Social Progress, Chinese University of Hong Kong

    11 - 15 May 2026

    Applied Research Methods for Social Scientists with James F. Downes, Center for Research and Social Progress, Chinese University of Hong Kong https://dresa.org.au/events/applied-research-methods-for-social-scientists-with-james-f-downes-center-for-research-and-social-progress-chinese-university-of-hong-kong-f2cb94c0-1fcf-44b2-ae5e-360dafeace2f This interactive, practical course bridges theory with contemporary social-science research and policy. The course is geared towards graduate students, academics, and policy researchers by covering key Qualitative and Quantitative Methods in Social Science and Policy Analysis. Participants will learn how to design and conduct Social Science research, interpret findings in real-world contexts, and explore examples from Comparative Politics, European Politics, Chinese Politics (China’s Belt & Road Initiative), and important policy issues such as Populism, Immigration, Climate Change, and EU Governance. 2026-05-11 18:00:00 UTC 2026-05-15 20:00:00 UTC James F. Downes, Center for Research and Social Progress, Chinese University of Hong Kong Instats info@instats.org [] [] [] open_to_all []

  • Generalised Linear Models using R with PR Stats,

    13 - 17 January 2026

    Generalised Linear Models using R with PR Stats, https://dresa.org.au/events/generalised-linear-models-using-r-with-pr-stats Generalised Linear Models using R is an intensive workshop for PhD students, professors and researchers that combines statistical theory with hands‑on R/RStudio practice to analyse non‑normal data—including counts, binary outcomes, proportions, categorical responses and skewed non‑negative variables. You will learn to fit, diagnose and interpret GLMs (Poisson, negative binomial, logistic, multinomial/ordinal, Gamma), apply extensions like zero‑inflation, mixed‑effects and Bayesian models (e.g., brms), and produce reproducible, publication‑quality code, figures and reporting for research outputs. 2026-01-13 01:00:00 UTC 2026-01-17 07:00:00 UTC PR Stats, Instats info@instats.org [] [] [] open_to_all []

  • Statistical Analysis of Social Network Data with Tianxi Li, School of Statistics, University of Minnesota, Twin Cities

    16 January 2026

    Statistical Analysis of Social Network Data with Tianxi Li, School of Statistics, University of Minnesota, Twin Cities https://dresa.org.au/events/statistical-analysis-of-social-network-data-with-tianxi-li-school-of-statistics-university-of-minnesota-twin-cities This hands-on seminar introduces modern statistical methods for social network data, from network fundamentals to advanced statistical network models and privacy considerations. Through reproducible R demonstrations, you will learn to implement and diagnose models, design valid tests for relational data, and apply principled, publishable workflows for high-impact network research. 2026-01-16 01:30:00 UTC 2026-01-16 09:30:00 UTC Tianxi Li, School of Statistics, University of Minnesota, Twin Cities Instats info@instats.org [] [] [] open_to_all []

  • Statistical Analysis of Social Network Data with Tianxi Li, School of Statistics, University of Minnesota, Twin Cities

    16 January 2026

    Statistical Analysis of Social Network Data with Tianxi Li, School of Statistics, University of Minnesota, Twin Cities https://dresa.org.au/events/statistical-analysis-of-social-network-data-with-tianxi-li-school-of-statistics-university-of-minnesota-twin-cities-408f808c-d710-444d-8ed1-dba6c4365da4 This hands-on seminar introduces modern statistical methods for social network data, from network fundamentals to advanced statistical network models and privacy considerations. Through reproducible R demonstrations, you will learn to implement and diagnose models, design valid tests for relational data, and apply principled, publishable workflows for high-impact network research. 2026-01-16 01:30:00 UTC 2026-01-16 09:30:00 UTC Tianxi Li, School of Statistics, University of Minnesota, Twin Cities Instats info@instats.org [] [] [] open_to_all []

  • Macroecology Using R with Renan Maestri, Department of Ecology, Universidade Federal do Rio Grande do Sul

    12 - 17 January 2026

    Macroecology Using R with Renan Maestri, Department of Ecology, Universidade Federal do Rio Grande do Sul https://dresa.org.au/events/macroecology-using-r-with-renan-maestri-department-of-ecology-universidade-federal-do-rio-grande-do-sul This hands-on workshop trains researchers to turn large geographic, trait, and phylogenetic datasets into rigorous, reproducible analyses and publication-quality maps and metrics of biodiversity across space and time using R. Participants will learn practical R workflows for spatial data manipulation, grid-based diversity and phylogenetic metrics, biogeographic regionalization, and estimation of historical dispersal and diversification—skills immediately applicable to thesis chapters, manuscripts, and comparative studies. 2026-01-12 23:00:00 UTC 2026-01-17 03:00:00 UTC Renan Maestri, Department of Ecology, Universidade Federal do Rio Grande do Sul Instats info@instats.org [] [] [] open_to_all []

  • Longitudinal Data Analysis and Growth Curve Models with Department of Epidemiology and Public Health, University College London

    11 - 13 February 2026

    Longitudinal Data Analysis and Growth Curve Models with Department of Epidemiology and Public Health, University College London https://dresa.org.au/events/longitudinal-data-analysis-and-growth-curve-models-with-department-of-epidemiology-and-public-health-university-college-london This two-day workshop provides a comprehensive exploration of mixed models and growth curves, focusing on the practical application of these methods in Stata and R for analyzing longitudinal data. Participants will gain essential skills in specifying, fitting, and interpreting mixed models, enhancing their research capabilities in fields such as psychology, sociology, and public health. 2026-02-11 20:00:00 UTC 2026-02-13 00:00:00 UTC Department of Epidemiology and Public Health, University College London Instats info@instats.org [] [] [] open_to_all []

  • Questionnaire Design Principles and Practices with Surette van Staden, Institute for Teacher Education, University of Innsbruck

    13 January 2026

    Questionnaire Design Principles and Practices with Surette van Staden, Institute for Teacher Education, University of Innsbruck https://dresa.org.au/events/questionnaire-design-principles-and-practices-with-surette-van-staden-institute-for-teacher-education-university-of-innsbruck This intensive seminar covers principles and practical steps for designing high-quality questionnaires — from translating conceptual frameworks into measurable constructs and writing unbiased, cross-culturally equivalent items to translation, cognitive pretesting, piloting, and linking instruments to scaling and analytic strategies — illustrated with examples from PIRLS and other international large-scale assessments (ILSAs). Designed for PhD students, post‑docs, faculty, and applied researchers, it emphasizes hands‑on application so you leave with prioritized item revisions, draft items and piloting protocols (including cognitive interview templates), and a clearer plan for how questionnaire decisions affect validity, reliability, and downstream analyses. 2026-01-13 01:00:00 UTC 2026-01-13 02:00:00 UTC Surette van Staden, Institute for Teacher Education, University of Innsbruck Instats info@instats.org [] [] [] open_to_all []

  • Causal Inference with AI and Machine Learning with Jason Anastasopoulos, School of Public and International Affairs, University of Georgia

    31 January - 3 February 2026

    Causal Inference with AI and Machine Learning with Jason Anastasopoulos, School of Public and International Affairs, University of Georgia https://dresa.org.au/events/causal-inference-with-ai-and-machine-learning-with-jason-anastasopoulos-school-of-public-and-international-affairs-university-of-georgia-686a3465-cca3-45ef-8bd5-1b943b5882d0 This seminar is designed for researchers, practitioners, and policymakers who want to move beyond prediction to understand cause-and-effect relationships. It introduces the foundations of causal inference—randomized trials, natural experiments, and causal-effect estimation—and shows how modern machine learning and AI methods enhance these tools for complex data. Participants will learn basic causal inference techniques and more advanced methods such as double machine learning, causal forests, and synthetic control approaches, while also engaging with applications to real-world problems. By the end, participants will be familiar with modern tools of causal inference and how to leverage LLMs to ensure robust and unbiased identification. 2026-01-31 03:30:00 UTC 2026-02-03 09:30:00 UTC Jason Anastasopoulos, School of Public and International Affairs, University of Georgia Instats info@instats.org [] [] [] open_to_all []

  • Foundations of Statistical Models and Linear Regression with Centre for Applied Statistics Courses (CASC), University College London

    26 - 29 January 2026

    Foundations of Statistical Models and Linear Regression with Centre for Applied Statistics Courses (CASC), University College London https://dresa.org.au/events/foundations-of-statistical-models-and-linear-regression-with-centre-for-applied-statistics-courses-casc-university-college-london This three-day workshop provides a comprehensive introduction to regression analysis, focusing on practical application using software such as Stata, R, and SPSS. Participants will gain essential skills for conducting robust regression analyses, interpreting results, and solving common data issues, all of which are crucial for advancing academic and professional research in various fields. 2026-01-26 20:30:00 UTC 2026-01-29 04:00:00 UTC Centre for Applied Statistics Courses (CASC), University College London Instats info@instats.org [] [] [] open_to_all []

  • Nonlinear Structural Equation Modeling with Holmes Finch, Department of Educational Psychology - Ball State University

    10 January 2026

    Nonlinear Structural Equation Modeling with Holmes Finch, Department of Educational Psychology - Ball State University https://dresa.org.au/events/nonlinear-structural-equation-modeling-with-holmes-finch-department-of-educational-psychology-ball-state-university This seminar provides researchers with the theoretical framework and hands-on implementation needed to specify, estimate, and interpret complex nonlinear relationships among latent variables in R and Mplus. The nonlinear effects include latent variable interactions, quadratic relationships among latent variables, nonlinear growth, and splines for latent variable models. Participants will learn the statistical frameworks underlying these models and will be provided with reproducible software scripts. The seminar concludes with advice on how to effectively present the results of nonlinear latent variable models. The focus throughout is on application and interpretation of the models. 2026-01-10 00:00:00 UTC 2026-01-10 08:00:00 UTC Holmes Finch, Department of Educational Psychology - Ball State University Instats info@instats.org [] [] [] open_to_all []

  • Analyzing Complex Survey Data with Brady West, Survey Research Center, Institute for Social Research, University of Michigan

    8 - 10 January 2026

    Analyzing Complex Survey Data with Brady West, Survey Research Center, Institute for Social Research, University of Michigan https://dresa.org.au/events/analyzing-complex-survey-data-with-brady-west-survey-research-center-institute-for-social-research-university-of-michigan This practical, hands-on seminar teaches researchers how to analyze complex sample survey data by correctly accounting for stratification, clustering, multi-stage sampling, and weighting to produce valid estimates, variances, tests, and inferences. Through guided exercises in R (RStudio), SAS, and Stata, participants learn survey-weighted estimation, Taylor-linearization and replicate-based variance methods, design- and model-based inference, multiple imputation that respects sample design features, and reproducible workflows directly applicable to dissertations, grants, and publications. 2026-01-08 03:00:00 UTC 2026-01-10 09:00:00 UTC Brady West, Survey Research Center, Institute for Social Research, University of Michigan Instats info@instats.org [] [] [] open_to_all []

  • Introduction to Spatial Econometrics with Edward Goldring, School of Social and Political Sciences, University of Melbourne

    12 - 16 January 2026

    Introduction to Spatial Econometrics with Edward Goldring, School of Social and Political Sciences, University of Melbourne https://dresa.org.au/events/introduction-to-spatial-econometrics-with-edward-goldring-school-of-social-and-political-sciences-university-of-melbourne-004a7cca-e9df-48d8-b341-25be2afa5499 This seminar provides the knowledge and tools to apply spatial econometric models, addressing how crucial spatial dynamics in politics are often omitted from standard statistical analysis. It is a hands-on seminar where participants will gain practical experience estimating these models to help them answer theoretically significant and policy-relevant questions. 2026-01-12 08:30:00 UTC 2026-01-16 10:30:00 UTC Edward Goldring, School of Social and Political Sciences, University of Melbourne Instats info@instats.org [] [] [] open_to_all []

  • From Peer Reviewing to Editing Journals with Carlton Fong, Department of Curriculum and Instruction, Texas State University

    9 January 2026

    From Peer Reviewing to Editing Journals with Carlton Fong, Department of Curriculum and Instruction, Texas State University https://dresa.org.au/events/from-peer-reviewing-to-editing-journals-with-carlton-fong-department-of-curriculum-and-instruction-texas-state-university "From Peer Reviewing to Editing Journals" trains researchers to move from reactive gatekeeping to proactive editorial leadership by teaching rigorous, efficient review practices and concrete pathways into editorial roles. Participants leave with evidence-based review workflows, templates, ethical guidance, and an actionable plan to translate reviewing into visible, field-shaping scholarly service across disciplines. 2026-01-09 03:00:00 UTC 2026-01-09 07:30:00 UTC Carlton Fong, Department of Curriculum and Instruction, Texas State University Instats info@instats.org [] [] [] open_to_all []

  • Introduction to Logistic Regression with Centre for Applied Statistics Courses (CASC), University College London

    9 - 10 February 2026

    Introduction to Logistic Regression with Centre for Applied Statistics Courses (CASC), University College London https://dresa.org.au/events/introduction-to-logistic-regression-with-centre-for-applied-statistics-courses-casc-university-college-london-93a739d2-1483-40cb-94c3-4507b3c4efda This one-day seminar provides a comprehensive introduction to logistic regression, a critical technique for analyzing binary outcome variables in various research fields. Participants will gain practical skills in data preparation, model fitting, and the interpretation of logistic regression outputs, enhancing their ability to tackle complex data analysis challenges in their academic work. 2026-02-09 20:30:00 UTC 2026-02-10 04:00:00 UTC Centre for Applied Statistics Courses (CASC), University College London Instats info@instats.org [] [] [] open_to_all []

  • Dealing with Missing Data with Centre for Applied Statistics Courses (CASC), University College London

    16 - 19 February 2026

    Dealing with Missing Data with Centre for Applied Statistics Courses (CASC), University College London https://dresa.org.au/events/dealing-with-missing-data-with-centre-for-applied-statistics-courses-casc-university-college-london This seminar provides a comprehensive introduction to dealing with missing data in research, covering essential concepts such as the types and reasons behind missing data, and effective/popular methods for addressing these issues, including multiple imputation and listwise deletion. Participants will enhance their analytical skills through a combination of theoretical knowledge and practical application, improving the credibility and reliability of their research findings. 2026-02-16 20:30:00 UTC 2026-02-19 04:00:00 UTC Centre for Applied Statistics Courses (CASC), University College London Instats info@instats.org [] [] [] open_to_all []

  • ANOVA and GLMs with SPSS with Centre for Applied Statistics Courses (CASC), University College London

    16 - 17 March 2026

    ANOVA and GLMs with SPSS with Centre for Applied Statistics Courses (CASC), University College London https://dresa.org.au/events/anova-and-glms-with-spss-with-centre-for-applied-statistics-courses-casc-university-college-london-34148615-ff5e-44d2-82d9-d3a5e5c62e72 The "ANOVA and GLMs with SPSS" workshop by the Centre for Applied Statistics Courses (CASC) at University College London is a comprehensive exploration of ANOVA and General Linear Models, designed for PhD students, professors, and professional researchers in various fields. This course will introduce you to the basic principles of ANOVA and GLMs, and how to choose, run, interpret, and report a variety of different models. The course takes a hands-on approach to learning, with SPSS software used for demonstration and practice throughout. 2026-03-16 20:30:00 UTC 2026-03-17 04:00:00 UTC Centre for Applied Statistics Courses (CASC), University College London Instats info@instats.org [] [] [] open_to_all []

  • From Peer Reviewing to Editing Journals with Carlton Fong, Department of Curriculum and Instruction, Texas State University

    9 January 2026

    From Peer Reviewing to Editing Journals with Carlton Fong, Department of Curriculum and Instruction, Texas State University https://dresa.org.au/events/from-peer-reviewing-to-editing-journals-with-carlton-fong-department-of-curriculum-and-instruction-texas-state-university-1859da3e-8772-407a-a6dc-cfea6605edcb "From Peer Reviewing to Editing Journals" trains researchers to move from reactive gatekeeping to proactive editorial leadership by teaching rigorous, efficient review practices and concrete pathways into editorial roles. Participants leave with evidence-based review workflows, templates, ethical guidance, and an actionable plan to translate reviewing into visible, field-shaping scholarly service across disciplines. 2026-01-09 03:00:00 UTC 2026-01-09 07:30:00 UTC Carlton Fong, Department of Curriculum and Instruction, Texas State University Instats info@instats.org [] [] [] open_to_all []

  • Data Management and Statistical Analysis with SPSS with Centre for Applied Statistics Courses (CASC), University College London

    30 - 31 January 2026

    Data Management and Statistical Analysis with SPSS with Centre for Applied Statistics Courses (CASC), University College London https://dresa.org.au/events/data-management-and-statistical-analysis-with-spss-with-centre-for-applied-statistics-courses-casc-university-college-london The "Introduction to SPSS" workshop by the Centre for Applied Statistics Courses (CASC) at University College London is a comprehensive course designed to equip researchers from various fields with the skills to perform data analysis using SPSS. This course offers an introduction to the uses and functions of the statistical software SPSS including data entry and editing, and the basics of analyses and graphs. 2026-01-30 20:30:00 UTC 2026-01-31 04:00:00 UTC Centre for Applied Statistics Courses (CASC), University College London Instats info@instats.org [] [] [] open_to_all []

  • Excel Methods for Power & Sample Size with Centre for Applied Statistics Courses (CASC), University College London

    3 - 4 February 2026

    Excel Methods for Power & Sample Size with Centre for Applied Statistics Courses (CASC), University College London https://dresa.org.au/events/excel-methods-for-power-sample-size-with-centre-for-applied-statistics-courses-casc-university-college-london The "Excel Methods for Power & Sample Size" workshop by the Centre for Applied Statistics Courses (CASC) at University College London is a comprehensive seminar designed to equip researchers with the necessary skills to conduct robust research. The seminar gives the basics of sample size estimation and will be of use to those embarking on a research project, and to those who are trying to complete ethics and grant applications. 2026-02-03 20:30:00 UTC 2026-02-04 04:00:00 UTC Centre for Applied Statistics Courses (CASC), University College London Instats info@instats.org [] [] [] open_to_all []

  • Excel Methods for Power & Sample Size with Centre for Applied Statistics Courses (CASC), University College London

    3 - 4 February 2026

    Excel Methods for Power & Sample Size with Centre for Applied Statistics Courses (CASC), University College London https://dresa.org.au/events/excel-methods-for-power-sample-size-with-centre-for-applied-statistics-courses-casc-university-college-london-5b929c29-d443-4e68-b0da-16f9c2a525d3 The "Excel Methods for Power & Sample Size" workshop by the Centre for Applied Statistics Courses (CASC) at University College London is a comprehensive seminar designed to equip researchers with the necessary skills to conduct robust research. The seminar gives the basics of sample size estimation and will be of use to those embarking on a research project, and to those who are trying to complete ethics and grant applications. 2026-02-03 20:30:00 UTC 2026-02-04 04:00:00 UTC Centre for Applied Statistics Courses (CASC), University College London Instats info@instats.org [] [] [] open_to_all []

  • Chi-Square and Beyond for 2x2 Tables with Centre for Applied Statistics Courses (CASC), University College London

    20 - 21 February 2026

    Chi-Square and Beyond for 2x2 Tables with Centre for Applied Statistics Courses (CASC), University College London https://dresa.org.au/events/chi-square-and-beyond-for-2x2-tables-with-centre-for-applied-statistics-courses-casc-university-college-london The "Chi-Square and Beyond for 2x2 Tables" workshop by the Centre for Applied Statistics Courses (CASC) at University College London offers a comprehensive understanding of the chi-square test and its advanced applications. The workshop is designed for PhD students, professors, and professional researchers, providing a balance of theoretical knowledge and practical application, enhancing research capabilities and broadening the statistical toolkit. The seminar demystifies the range of statistics that can be used to summarise the associations between two binary variables, moving on from standard chi-square test to investigate other options that may yield more useful information. 2026-02-20 20:30:00 UTC 2026-02-21 04:00:00 UTC Centre for Applied Statistics Courses (CASC), University College London Instats info@instats.org [] [] [] open_to_all []

  • Assessing Reliability and Validity with Centre for Applied Statistics Courses (CASC), University College London

    23 - 24 March 2026

    Assessing Reliability and Validity with Centre for Applied Statistics Courses (CASC), University College London https://dresa.org.au/events/assessing-reliability-and-validity-with-centre-for-applied-statistics-courses-casc-university-college-london This workshop, offered by the Centre for Applied Statistics Courses (CASC) at University College London, provides a comprehensive understanding of reliability and validity in academic research. The seminar offers an introduction to the principles, methods of assessment, and the appropriateness of statistical analyses for different types of measurement validity and reliability. Particular focus is given to statistical assessment of reliability over time, contexts and raters. 2026-03-23 20:30:00 UTC 2026-03-24 04:00:00 UTC Centre for Applied Statistics Courses (CASC), University College London Instats info@instats.org [] [] [] open_to_all []

  • Introduction to Survival Analysis & Cox Regression with Centre for Applied Statistics Courses (CASC), University College London

    3 - 4 March 2026

    Introduction to Survival Analysis & Cox Regression with Centre for Applied Statistics Courses (CASC), University College London https://dresa.org.au/events/introduction-to-survival-analysis-cox-regression-with-centre-for-applied-statistics-courses-casc-university-college-london This seminar offers a complete introduction to survival analysis, also known as time-to-event data modeling. Log-rank tests, Cox proportional hazard regression models and other key topics will be covered in depth to determine associations between predictors and event occurrence. 2026-03-03 20:30:00 UTC 2026-03-04 04:00:00 UTC Centre for Applied Statistics Courses (CASC), University College London Instats info@instats.org [] [] [] open_to_all []

  • Power and Sample Size in Excel with Centre for Applied Statistics Courses (CASC), University College London

    3 - 4 February 2026

    Power and Sample Size in Excel with Centre for Applied Statistics Courses (CASC), University College London https://dresa.org.au/events/power-and-sample-size-in-excel-with-centre-for-applied-statistics-courses-casc-university-college-london The "Excel Methods for Power & Sample Size" workshop by the Centre for Applied Statistics Courses (CASC) at University College London is a comprehensive seminar designed to equip researchers with the necessary skills to conduct robust research. The seminar gives the basics of sample size estimation and will be of use to those embarking on a research project, and to those who are trying to complete ethics and grant applications. 2026-02-03 20:30:00 UTC 2026-02-04 04:00:00 UTC Centre for Applied Statistics Courses (CASC), University College London Instats info@instats.org [] [] [] open_to_all []

  • Survival Analysis and Cox Regression with Centre for Applied Statistics Courses (CASC), University College London

    3 - 4 March 2026

    Survival Analysis and Cox Regression with Centre for Applied Statistics Courses (CASC), University College London https://dresa.org.au/events/survival-analysis-and-cox-regression-with-centre-for-applied-statistics-courses-casc-university-college-london This seminar offers a complete introduction to survival analysis, also known as time-to-event data modeling. Log-rank tests, Cox proportional hazard regression models and other key topics will be covered in depth to determine associations between predictors and event occurrence. 2026-03-03 20:30:00 UTC 2026-03-04 04:00:00 UTC Centre for Applied Statistics Courses (CASC), University College London Instats info@instats.org [] [] [] open_to_all []

  • AI-Powered Business Analytics for Researchers with Martin Qiu, Lazaridis School of Business and Economics, Wilfrid Laurier University

    15 - 16 May 2026

    AI-Powered Business Analytics for Researchers with Martin Qiu, Lazaridis School of Business and Economics, Wilfrid Laurier University https://dresa.org.au/events/ai-powered-business-analytics-for-researchers-with-martin-qiu-lazaridis-school-of-business-and-economics-wilfrid-laurier-university-6083dffa-b307-48ca-ab90-e05738c942e3 This four-session workshop bridges the gap between established research methods and modern business-analytics techniques. It prepares you for a non-academic "Plan B" career path that is both intellectually stimulating and professionally rewarding. You'll learn how familiar stats tools like regression, experimental design, and hypothesis testing map onto supervised and unsupervised machine learning, data mining, and predictive analytics workflows. The workshop focuses on practical implementation using [b]R (or Python)[/b] and [b]Tableau[/b], with AI-supported coding to streamline routine tasks and provide a foundation for your expanding skill development. This will prepare you for diverse opportunities in both academia and industry. 2026-05-15 19:00:00 UTC 2026-05-16 01:00:00 UTC Martin Qiu, Lazaridis School of Business and Economics, Wilfrid Laurier University Instats info@instats.org [] [] [] open_to_all []

  • Introduction to Mixed Methods Research: From Theory to Practice with Sergi Fabregues, Department of Psychology and Education, Universitat Oberta de Catalunya and Mixed Methods Program, University of Michigan

    10 February - 12 March 2026

    Introduction to Mixed Methods Research: From Theory to Practice with Sergi Fabregues, Department of Psychology and Education, Universitat Oberta de Catalunya and Mixed Methods Program, University of Michigan https://dresa.org.au/events/introduction-to-mixed-methods-research-from-theory-to-practice-with-sergi-fabregues-department-of-psychology-and-education-universitat-oberta-de-catalunya-and-mixed-methods-program-university-of-michigan-4dfd4b30-894f-4caf-bf79-4fe445a35bf4 This seminar provides a comprehensive introduction to mixed methods research, integrating both qualitative and quantitative approaches to offer a deeper understanding of complex research questions. Participants will gain theoretical knowledge and practical skills in designing, conducting, and analyzing mixed methods studies, enhancing their research capabilities across various academic fields. 2026-02-10 01:30:00 UTC 2026-03-12 05:00:00 UTC Sergi Fabregues, Department of Psychology and Education, Universitat Oberta de Catalunya and Mixed Methods Program, University of Michigan Instats info@instats.org [] [] [] open_to_all []

  • Using Experiments in Applied Economics with Sebastian Galiani, Department of Economics, University of Maryland

    20 - 28 March 2026

    Using Experiments in Applied Economics with Sebastian Galiani, Department of Economics, University of Maryland https://dresa.org.au/events/using-experiments-in-applied-economics-with-sebastian-galiani-department-of-economics-university-of-maryland This four-day workshop provides an in-depth exploration of experimental methods in applied economics, focusing on the identification and interpretation of causal effects to enhance empirical research outcomes. Participants will gain skills in designing rigorous experiments and applying economic theory, preparing them to conduct impactful and ethically sound research in academic and policy contexts. 2026-03-20 00:00:00 UTC 2026-03-28 03:30:00 UTC Sebastian Galiani, Department of Economics, University of Maryland Instats info@instats.org [] [] [] open_to_all []

  • Supply Chain Demand Prediction with Python with Isik Bicer, Schulich School of Business, York University

    20 - 24 January 2026

    Supply Chain Demand Prediction with Python with Isik Bicer, Schulich School of Business, York University https://dresa.org.au/events/supply-chain-demand-prediction-with-python-with-isik-bicer-schulich-school-of-business-york-university This workshop brings together statistics, machine learning, and operations research to address modern demand‑forecasting challenges through rigorous theory and hands‑on Python practice covering tailored regression and regularization, time‑series methods, probabilistic forecasting, classification for product selection, and simulation‑based uncertainty modeling. Aimed at PhD students, faculty, and researchers, it trains participants to build reproducible, research‑ready Python implementations, apply principled model evaluation and experimental design, and produce simulation and empirical studies suitable for dissertation work and peer‑reviewed publication. 2026-01-20 02:00:00 UTC 2026-01-24 03:30:00 UTC Isik Bicer, Schulich School of Business, York University Instats info@instats.org [] [] [] open_to_all []

  • Demand Prediction with Python with Isik Bicer, Schulich School of Business, York University

    20 - 24 January 2026

    Demand Prediction with Python with Isik Bicer, Schulich School of Business, York University https://dresa.org.au/events/demand-prediction-with-python-with-isik-bicer-schulich-school-of-business-york-university This workshop brings together statistics, machine learning, and operations research to address modern demand‑forecasting challenges through rigorous theory and hands‑on Python practice covering tailored regression and regularization, time‑series methods, probabilistic forecasting, classification for product selection, and simulation‑based uncertainty modeling. Aimed at PhD students, faculty, and researchers, it trains participants to build reproducible, research‑ready Python implementations, apply principled model evaluation and experimental design, and produce simulation and empirical studies suitable for dissertation work and peer‑reviewed publication. 2026-01-20 02:00:00 UTC 2026-01-24 03:30:00 UTC Isik Bicer, Schulich School of Business, York University Instats info@instats.org [] [] [] open_to_all []

  • Researching Crowdfunding with Douglas Cumming, College of Business, Florida Atlantic University

    28 January - 25 February 2026

    Researching Crowdfunding with Douglas Cumming, College of Business, Florida Atlantic University https://dresa.org.au/events/researching-crowdfunding-with-douglas-cumming-college-of-business-florida-atlantic-university-2228dbf7-e45f-4ada-9c84-3dbc88f6a41f This comprehensive seminar delves into the intricacies of crowdfunding, focusing on rewards, equity, and debt-based models, providing a deep understanding of their operations, challenges, and opportunities within the financial ecosystem. Led by an esteemed expert, participants will gain insights into agency problems, valuation techniques, governance models, and regulatory issues, enabling them to conduct impactful research in the crowdfunding domain. 2026-01-28 08:00:00 UTC 2026-02-25 11:00:00 UTC Douglas Cumming, College of Business, Florida Atlantic University Instats info@instats.org [] [] [] open_to_all []

  • Causal AI for Real-World Data with Andy Wilson, Spencer Fox Eccles School of Medicine, University of Utah

    20 January 2026

    Causal AI for Real-World Data with Andy Wilson, Spencer Fox Eccles School of Medicine, University of Utah https://dresa.org.au/events/causal-ai-for-real-world-data-with-andy-wilson-spencer-fox-eccles-school-of-medicine-university-of-utah Causal AI for Real-World Data provides a compact, rigorous, hands‑on treatment of contemporary causal inference, guiding researchers from question specification and DAG‑based identification to defensible estimation and sensitivity analysis of observational health data. Participants will learn to apply the Causal Roadmap and implement state‑of‑the‑art tools in R and Python — including DAG construction and causal discovery, propensity methods, g‑computation, TMLE with SuperLearner, double machine learning, and VAE‑based generative validation — and leave with reproducible artifacts to support transparent, peer‑reviewable causal claims. 2026-01-20 14:00:44 UTC 2026-01-20 20:00:44 UTC Andy Wilson, Spencer Fox Eccles School of Medicine, University of Utah Instats info@instats.org [] [] [] open_to_all []

  • Causal AI for Real-World Data with Andy Wilson, Spencer Fox Eccles School of Medicine, University of Utah

    21 January 2026

    Causal AI for Real-World Data with Andy Wilson, Spencer Fox Eccles School of Medicine, University of Utah https://dresa.org.au/events/causal-ai-for-real-world-data-with-andy-wilson-spencer-fox-eccles-school-of-medicine-university-of-utah-75820d48-0fb6-4c66-af9a-dda464ce62b2 Causal AI for Real-World Data provides a compact, rigorous, hands‑on treatment of contemporary causal inference, guiding researchers from question specification and DAG‑based identification to defensible estimation and sensitivity analysis of observational health data. Participants will learn to apply the Causal Roadmap and implement state‑of‑the‑art tools in R and Python — including DAG construction and causal discovery, propensity methods, g‑computation, TMLE with SuperLearner, double machine learning, and VAE‑based generative validation — and leave with reproducible artifacts to support transparent, peer‑reviewable causal claims. 2026-01-21 03:00:00 UTC 2026-01-21 07:30:00 UTC Andy Wilson, Spencer Fox Eccles School of Medicine, University of Utah Instats info@instats.org [] [] [] open_to_all []

  • Causal AI for Real-World Data with Andy Wilson, Spencer Fox Eccles School of Medicine, University of Utah

    20 January 2026

    Causal AI for Real-World Data with Andy Wilson, Spencer Fox Eccles School of Medicine, University of Utah https://dresa.org.au/events/causal-ai-for-real-world-data-with-andy-wilson-spencer-fox-eccles-school-of-medicine-university-of-utah-2cda1071-5775-4279-a680-b1f8ed1ffc30 Causal AI for Real-World Data provides a compact, rigorous, hands‑on treatment of contemporary causal inference, guiding researchers from question specification and DAG‑based identification to defensible estimation and sensitivity analysis of observational health data. Participants will learn to apply the Causal Roadmap and implement state‑of‑the‑art tools in R and Python — including DAG construction and causal discovery, propensity methods, g‑computation, TMLE with SuperLearner, double machine learning, and VAE‑based generative validation — and leave with reproducible artifacts to support transparent, peer‑reviewable causal claims. 2026-01-20 03:00:00 UTC 2026-01-20 07:30:00 UTC Andy Wilson, Spencer Fox Eccles School of Medicine, University of Utah Instats info@instats.org [] [] [] open_to_all []

  • Egocentric Social Network Analysis with Bryce Hughes, Adult and Higher Education, Montana State University

    24 - 25 January 2026

    Egocentric Social Network Analysis with Bryce Hughes, Adult and Higher Education, Montana State University https://dresa.org.au/events/egocentric-social-network-analysis-with-bryce-hughes-adult-and-higher-education-montana-state-university This two-day hands-on workshop introduces researchers to egocentric social network analysis (SNA) using Stata, combining conceptual foundations with practical applications. Participants will work with real survey data and case studies to design ego-network surveys, clean and analyze data, compute key network metrics, and integrate them into regression models. Supplementary annotated code and resources, including examples of advanced techniques, will also be provided. 2026-01-24 05:00:00 UTC 2026-01-25 10:00:00 UTC Bryce Hughes, Adult and Higher Education, Montana State University Instats info@instats.org [] [] [] open_to_all []

  • Ethnography in Risky Settings with Tobias Marschall, Graduate Institute Geneva

    26 - 28 February 2026

    Ethnography in Risky Settings with Tobias Marschall, Graduate Institute Geneva https://dresa.org.au/events/ethnography-in-risky-settings-with-tobias-marschall-graduate-institute-geneva-76dccf6b-eea1-492a-99a0-543d7a4c7c4c This workshop examines the ethical and political demands of ethnography in risky settings, where danger and uncertainty often push work beyond procedural ethics. Building on ethnography’s pursuit of cultural intimacy and thick description, we treat accuracy, authenticity, and truthfulness as contested criteria and trace how realism vs. fiction, visibility and form, intensified image circulation, and tightening border regimes reshape practice. Through discussion, case analyses, and structured debates, participants explore informed consent, participation, “do no harm,” and authorship. We also consider alternative publication modalities and reflect on researchers’ multiple roles and the ethical stakes of long-term engagement in contexts of risk and vulnerability. 2026-02-26 04:30:00 UTC 2026-02-28 07:00:00 UTC Tobias Marschall, Graduate Institute Geneva Instats info@instats.org [] [] [] open_to_all []