John W. Tukey
Impact in
- Statistics and Probability top 0.01%
- Advanced Statistical Methods and Models
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Statistical Methods in Clinical Trials
- Statistics, Probability and Uncertainty top 0.02%
- Advanced Statistical Process Monitoring
Papers in
-
- Advanced Statistical Methods and Models 26
- Statistical Methods in Clinical Trials 14
- Statistical Methods and Inference 7
- Statistical Methods and Bayesian Inference 6
- Co-authors
- F. N. David (1 shared paper)J.W. Cooley (2 shared papers)Frederick Mosteller (29 shared papers)David C. Hoaglin (18 shared papers)James R. Beniger (1 shared paper)R. B. Blackman (4 shared papers)John Osborn (2 shared papers)Robert McGill (2 shared papers)
- Journals
- Journal of the American Statistical Association (34 papers)Technometrics (27 papers)The American Statistician (16 papers)Biometrics (14 papers)Biometrika (7 papers)
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
John W. Tukey
222 papers receiving 47.0k citations
John W. Tukey's Hit Papers
Peers
Comparison fields: 5 of 246
- Statistics and Probability 8.0k
- Statistics, Probability and Uncertainty 3.2k
- Signal Processing 3.9k
- Management Science and Operations Research 3.0k
- Computer Vision and Pattern Recognition 4.6k
Countries citing papers authored by John W. Tukey
This map shows the geographic impact of John W. Tukey'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 John W. Tukey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John W. Tukey more than expected).
Fields of papers citing papers by John W. Tukey
This network shows the impact of papers produced by John W. Tukey. 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 John W. Tukey. The network helps show where John W. Tukey may publish in the future.
Co-authors
The 25 scholars most cited alongside John W. Tukey, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 229 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Exploratory Data Analysis Hit paper breakdown → | 1977 | 9626 |
| 2 | An algorithm for the machine calculation of complex Fourier series Hit paper breakdown → | 1965 | 7638 |
| 3 | Exploratory Data Analysis. Hit paper breakdown → | 1978 | 1982 |
| 4 | Variations of Box Plots Hit paper breakdown → | 1978 | 1774 |
| 5 | The Measurement of Power Spectra Hit paper breakdown → | 1960 | 1513 |
| 6 | Understanding robust and exploratory data analysis Hit paper breakdown → | 1983 | 1472 |
| 7 | Data Analysis and Regression. Hit paper breakdown → | 1979 | 1372 |
| 8 | Simultaneous conjoint measurement: A new type of fundamental measurement Hit paper breakdown → | 1964 | 1296 |
| 9 | The Future of Data Analysis Hit paper breakdown → | 1962 | 1153 |
| 10 | Data Analysis and Regression: A Second Course in Statistics Hit paper breakdown → | 1977 | 1144 |
| 11 | Exploratory Data Analysis Hit paper breakdown → | 1978 | 1124 |
| 12 | Exploratory Data Analysis. Hit paper breakdown → | 1978 | 1019 |
| 13 | Data Analysis and Regression. Hit paper breakdown → | 1978 | 1017 |
| 14 | The Problem of Multiple Comparisons Hit paper breakdown → | 1953 | 1003 |
| 15 | Exploratory Data Analysis. Hit paper breakdown → | 1978 | 997 |
| 16 | A Projection Pursuit Algorithm for Exploratory Data Analysis Hit paper breakdown → | 1974 | 961 |
| 17 | Understanding Robust and Exploratory Data Analysis. Hit paper breakdown → | 1984 | 900 |
| 18 | Statistical Methods for Research Workers Hit paper breakdown → | 1952 | 864 |
| 19 | An Algorithm for the Machine Calculation of Complex Fourier Series Hit paper breakdown → | 1965 | 681 |
| 20 | The Fitting of Power Series, Meaning Polynomials, Illustrated on Band-Spectroscopic Data Hit paper breakdown → | 1974 | 681 |
About John W. Tukey
John W. Tukey is a scholar working on Statistics and Probability, Artificial Intelligence, Management Science and Operations Research, Statistics, Probability and Uncertainty and Information Systems, having authored 229 papers that have together received 52.9k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (26 papers), Statistical Methods in Clinical Trials (14 papers), Optimal Experimental Design Methods (11 papers), Data Mining Algorithms and Applications (7 papers), Statistical Methods and Inference (7 papers), Spectroscopy and Chemometric Analyses (6 papers), Statistical Methods and Bayesian Inference (6 papers) and Advanced Statistical Process Monitoring (6 papers). The work is most often cited by research in Statistics and Probability (8.0k citations), Statistics, Probability and Uncertainty (3.2k citations), Signal Processing (3.9k citations), Management Science and Operations Research (3.0k citations) and Computer Vision and Pattern Recognition (4.6k citations). John W. Tukey has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include F. N. David, J.W. Cooley, Frederick Mosteller, David C. Hoaglin, James R. Beniger, R. B. Blackman, John Osborn, Robert McGill, Wayne A. Larsen and R. Duncan Luce. Their work appears in journals such as Journal of the American Statistical Association, Technometrics, The American Statistician, Biometrics and Biometrika.
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.