All of Statistics: A Concise Course in Statistical Inference
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Wasserman (2004) is the first statistics textbook to treat Simpson's paradox in its correct causal context.
“Still, to the best of my knowledge, Wasserman (2004) is the first statistics textbook to treat Simpson's paradox in its correct causal context (Pearl, 2000a, p. 200).”
From Causal inference in statistics: An overview (2009) · cites this paper as Wasserman, 2004
Support vector machines with nonlinear kernels are well-suited for identifying neuronal subspaces in relation to specific task features and account for potential nonlinearities in the response properties of the neurons.
“As described previously 62–64, these approaches are well-suited for identifying neuronal ‘subspaces’ in relation to specific task features and account for potential nonlinearities in the response properties of the neurons.”
From Reduced sociability and social agency encoding in adult Shank3-mutant mice are restored through gene re-expression in real time (2021) · cites this paper as [62]
Cites
Härdle, W. K. (1991) · Springer series in statistics · doi:10.1007/978-1-4612-4432-5_2 · Cited by 12 · see citing works
Linear Regression and Logistic Regression
Chopra, D., & Khurana, R. (2023) · BENTHAM SCIENCE PUBLISHERS eBooks · doi:10.2174/9789815124422123010005 · Cited by 5 · see citing works
Knox, S. W. (2018) · Wiley series in probability and statistics · doi:10.1002/9781119439868.ch5 · Cited by 2 · see citing works
Probability Redux: Stochastic Processes
Wasserman, L. (2004) · Springer texts in statistics · doi:10.1007/978-0-387-21736-9_23 · Cited by 1 · see citing works
Self-citationSmoothing Using Orthogonal Functions
Wasserman, L. (2004) · Springer texts in statistics · doi:10.1007/978-0-387-21736-9_21 · Cited by 1 · see citing works
Self-citationHierarchical Log-Linear Models
George, D., & Mallery, P. (2024) · Routledge eBooks · doi:10.4324/9781032622156-28 · Cited by 1 · see citing works
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The Pascal Visual Object Classes Challenge: A Retrospective
Everingham, M., Eslami, S. M. A., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman, A. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-014-0733-5 · Cited by 7,139 · see citing works
Causal inference in statistics: An overview
Pearl, J. (2009) · Statistics Surveys · doi:10.1214/09-ss057 · Cited by 2,336 · see citing works
Statistical Evidence in Experimental Psychology: An Empirical Comparison Using 855 <i>t</i> Tests
Wetzels, R., Matzke, D., Lee, M. D., Rouder, J. N., Iverson, G. J., & Wagenmakers, E.-J. (2011) · Perspectives on Psychological Science · doi:10.1177/1745691611406923 · Cited by 945 · see citing works
An Introduction to Causal Inference
Pearl, J. (2010) · The International Journal of Biostatistics · doi:10.2202/1557-4679.1203 · Cited by 755 · see citing works
Han, B., & Eskin, E. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.04.014 · Cited by 680 · see citing works
“Learning factors analysis-a general method for cognitive model evaluation and improvement,”
Cen, H., Koedinger, K., & Junker, B. (2006) · Lecture notes in computer science · doi:10.1007/11774303_17 · Cited by 572 · see citing works
Quantum theory of superresolution for two incoherent optical point sources
Tsang, M., Nair, R., & Lu, X.-M. (2016) · Physical Review X · doi:10.1103/physrevx.6.031033 · Cited by 482 · see citing works
Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing
Kohavi, R., Tang, D., & Xu, Y. (2020) · doi:10.1017/9781108653985 · Cited by 297 · see citing works
Analyses of the Stability and Core Taxonomic Memberships of the Human Microbiome
Li, K., Bihan, M., & Methé, B. A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0063139 · Cited by 235 · see citing works
Bayesian State Estimation for Unobservable Distribution Systems Via Deep Learning
Mestav, K. R., Luengo-Rozas, J., & Tong, L. (2019) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2019.2919157 · Cited by 216 · see citing works
Yang, Y., & Kozloski, M. (2011) · The Journals of Gerontology: Series A · doi:10.1093/gerona/glr003 · Cited by 202 · see citing works
Natural Language Processing for EHR-Based Pharmacovigilance: A Structured Review
Luo, Y., Thompson, W. K., Herr, T. M., Zeng, Z., Berendsen, M. A., Jonnalagadda, S. R., Carson, M. B., & Starren, J. (2017) · Drug Safety · doi:10.1007/s40264-017-0558-6 · Cited by 200 · see citing works
A Reviewer’s Guide to Qualitative Rigor
Nowell, B., & Albrecht, K. (2019) · Journal of Public Administration Research and Theory · doi:10.1093/jopart/muy052 · Cited by 185 · see citing works
The role of causality in judgment under uncertainty
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Measuring the stability of results from supervised statistical learning
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Confidence Estimation for Object Detection in Document Images
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- Authors
- Wasserman, L.
- Affiliations
- Carnegie Mellon University (US)
- Corresponding author
- Wasserman, Larry
- ORCID
- Wasserman, Larry
- Venue
- Springer Texts in Statistics
- Publisher
- Springer New York
- Published
- 2004
- ISSN
- 1431-875X (ISSN-L)
- 2197-4136
- OpenAlex
- W4249875616
- Cited by
- 1,090
- References
- 6
- Citations by year
- 2026: 86 · 2025: 89 · 2024: 95 · 2023: 81 · 2022: 64 · 2021: 52 · 2020: 100 · 2019: 59 · 2018: 44 · 2017: 48 · 2016: 51 · 2015: 44 · 2014: 51 · 2013: 43 · 2012: 41
- FWCI
- 2.23
- Type
- book
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Springer texts in statistics (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
- Keywords
- statistics, probability theory, statistical inference, mathematical statistics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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