George W. Cobb
- Statistics and Probability top 0.2%
- Statistics Education and Methodologies 20
- Education top 2%
- Innovations in Educational Methods 4
- Artificial Intelligence top 5%
- Data Analysis with R 5
- Bayesian Modeling and Causal Inference 2
- Strategy and Management top 10%
- Corporate Social Responsibility Reporting 2
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- Big Data and Business Intelligence 1
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- Complex Systems and Decision Making 1
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- Aquatic Ecosystems and Biodiversity 1
- Co-authors
- David S. MooreDaniel W. SchaferFred L. RamseyDavid PowerLorna StevensonDavid CollisonYung-Pin ChenJoan Garfield
- Journals
- New England Journal of Medicine (1 paper)JAMA (1 paper)Journal of the American Statistical Association (4 papers)
- Partner nations
- United StatesUnited KingdomSweden
In The Last Decade
George W. Cobb
48 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 153
- Statistics and Probability 1.1k
- Education 526
- Statistics, Probability and Uncertainty 75
- Artificial Intelligence 293
- Strategy and Management 111
Countries citing papers authored by George W. Cobb
This map shows the geographic impact of George W. Cobb's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by George W. Cobb with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites George W. Cobb more than expected).
Fields of papers citing papers by George W. Cobb
This network shows the impact of papers produced by George W. Cobb. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by George W. Cobb. The network helps show where George W. Cobb may publish in the future.
Co-authorship network
The 25 scholars most cited alongside George W. Cobb, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Introduction to Statistical Investigations (2nd ed.) | 2019 | 0 |
| 2 | STAT2: Modeling with Regression and ANOVA | 2018 | 6 |
| 3 | 2015 | 68 | |
| 4 | 2015 | 27 | |
| 5 | STAT2: Building Models for a World of Data | 2012 | 11 |
| 6 | Statistics: From Data to Decision | 2009 | 11 |
| 7 | 2009 | 41 | |
| 8 | 2007 | 13 | |
| 9 | 2005 | 35 | |
| 10 | 2000 | 19 | |
| 11 | 1999 | 1 | |
| 12 | 1999 | 15 | |
| 13 | 1999 | 5 | |
| 14 | 1998 | 2 | |
| 15 | 1998 | 1 | |
| 16 | 1997 | 303 | |
| 17 | An electronic companion to business statistics | 1997 | 1 |
| 18 | 1995 | 13 | |
| 19 | 1993 | 93 | |
| 20 | 1987 | 3 |
About George W. Cobb
George W. Cobb is a scholar working on Statistics and Probability, General Decision Sciences and Transplantation, having authored 49 papers that have together received 1.8k indexed citations. Recurring topics across this work include Statistics Education and Methodologies (20 papers), Data Analysis with R (5 papers), Innovations in Educational Methods (4 papers), Bayesian Modeling and Causal Inference (2 papers), Corporate Social Responsibility Reporting (2 papers), Big Data and Business Intelligence (1 paper), Complex Systems and Decision Making (1 paper) and Aquatic Ecosystems and Biodiversity (1 paper). The work is most often cited by research in Statistics and Probability (1.1k citations), Education (526 citations) and Statistics, Probability and Uncertainty (75 citations). George W. Cobb has collaborated with scholars based in United States, United Kingdom and Sweden. Frequent co-authors include David S. Moore, Daniel W. Schafer, Fred L. Ramsey, David Power, Lorna Stevenson, David Collison, Yung-Pin Chen, Joan Garfield, William Q. Meeker and Clifford Konold. Their work appears in journals such as New England Journal of Medicine, JAMA and Journal of the American Statistical Association.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.