Statistical Modeling, Causal Inference, and Social Science
StatModeling is a blog dedicated to statistical modeling, Bayesian statistics, and data analysis. It provides insights, discussions, and tutorials on various statistical methods and their applications in real-world scenarios. The blog is maintained by Andrew Gelman, a professor of statistics and political science at Columbia University, and features contributions from other experts in the field.
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Domain Rating
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Domain Authority
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Citation Level
2004
English, etc
Website Key Features
Blog Posts
In-depth articles and discussions on statistical modeling and Bayesian statistics.
Tutorials
Step-by-step guides on statistical methods and data analysis techniques.
Research Highlights
Summaries and discussions of recent research papers in statistics and related fields.
Commentary
Opinions and commentary on current trends and issues in statistics and data science.
Guest Posts
Contributions from other experts in the field of statistics and data analysis.
Book Reviews
Reviews and discussions of books related to statistics, data science, and Bayesian analysis.
Software Recommendations
Recommendations and reviews of statistical software and tools.
Data Sets
Links to interesting and useful data sets for analysis and modeling.
Workshops and Courses
Information on upcoming workshops, courses, and seminars related to statistical modeling.
Q&A Section
A section for readers to ask questions and receive answers from the blog's contributors.
Additional information
Founder
Andrew Gelman, Professor of Statistics and Political Science at Columbia University.
Frequency of Updates
The blog is updated regularly, with new posts appearing several times a week.
Audience
The blog is aimed at statisticians, data scientists, researchers, and anyone interested in statistical modeling and Bayesian analysis.
Collaborations
The blog often features collaborations with other statisticians and researchers, providing a wide range of perspectives on statistical modeling.
Impact
StatModeling is widely recognized in the statistics and data science communities for its insightful analysis and contributions to the field.
HTTP headers
Security headers report is a very important part of user data protection. Learn more about http headers for statmodeling.stat.columbia.edu