Helen MacGillivray
- Statistics and Probability top 1%
- Artificial Intelligence top 10%
- Education top 10%
- Modeling and Simulation top 2%
- Finance top 5%
- Co-authors
- Kevin P. BalandaRobert KingTony CroftKerrie MengersenMichele HaynesBarry G. QuinnArthur L. SchwartzTimothy B. Erickson
- Topics
- Statistics Education and Methodologies (29 papers)Mathematics Education and Programs (12 papers)Data Analysis with R (8 papers)
- Partner nations
- AustraliaUnited KingdomUnited States
In The Last Decade
Helen MacGillivray
52 papers receiving 961 citations
Peers
Comparison fields: 5 of 144
- Statistics and Probability 462
- Artificial Intelligence 172
- Education 144
- Modeling and Simulation 137
- Finance 132
Countries citing papers authored by Helen MacGillivray
This map shows the geographic impact of Helen MacGillivray'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 Helen MacGillivray with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Helen MacGillivray more than expected).
Fields of papers citing papers by Helen MacGillivray
This network shows the impact of papers produced by Helen MacGillivray. 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 Helen MacGillivray. The network helps show where Helen MacGillivray may publish in the future.
Co-authorship network of co-authors of Helen MacGillivray
This figure shows the co-authorship network connecting the top 25 collaborators of Helen MacGillivray. A scholar is included among the top collaborators of Helen MacGillivray based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Helen MacGillivray. Helen MacGillivray is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | The SuperCOSMOS Science Archive | 1 |
| 11 | 9 | |
| 12 | The Gap between Assumed Skills and Reality in Mathematics Learning | 3 |
| 13 | 7 | |
| 14 | 2 | |
| 15 | 1 | |
| 16 | 49 | |
| 17 | 293 | |
| 18 | 4 | |
| 19 | 0 | |
| 20 | 3 |
About Helen MacGillivray
Helen MacGillivray is a scholar working on Statistics and Probability, Modeling and Simulation and Architecture, having authored 63 papers that have together received 1.1k indexed citations. Recurring topics across this work include Statistics Education and Methodologies (29 papers), Mathematics Education and Programs (12 papers) and Data Analysis with R (8 papers). The work is most often cited by research in Statistics and Probability (462 citations), Modeling and Simulation (137 citations) and Statistics, Probability and Uncertainty (121 citations). Helen MacGillivray has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Kevin P. Balanda, Robert King, Tony Croft, Kerrie Mengersen, Michele Haynes, Barry G. Quinn, Arthur L. Schwartz, Timothy B. Erickson, Ian J. Turner and Paul Hewson. Their work appears in journals such as Clinical Chemistry, The Annals of Statistics and The American Statistician.
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.