T. Alhuzali
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
T. Alhuzali has a total of 2 co-authors. Here are the top co-authors by number of shared publications:
E. Stojanovski
Affiliation School of Information & Physical Sciences, College of Engineering, Science and Environment, University of Newcastle, Callaghan NSW, Australia
1 shared publication- Eric J. Beh
National Institute for Applied Statistics Research Australia (NIASRA), University of Wollongong, Wollongong, Australia
1 shared publication
Latest Publications
- Open Access
- 1 April 2022
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 17 (4) , e0265929
Multiple correspondence analysis as a tool for examining Nobel Prize data from 1901 to 2018
The main goal of this paper is to examine Nobel Prize data by studying the association among the laureate’s country of birth or residence, discipline, time period in which the Nobel Prize was awarded, and gender of the recipient. Multiple correspondence analysis is used as a tool to examine the association between these four categorical variables by cross classifying them in the form of a four-way contingency table. The data that we examine comprise Nobel Prize recipients from 1901 to 2018 (inclusive) from eight-developed countries, with a total sample of 785 Nobel Prize recipients. The countries include Canada, France, Germany, Italy, Japan, Russia, the British Isles, and the USA and the disciplines in which the individuals were awarded the prizes include chemistry, physics, physiology or medicine, literature, economics, and peace.
- 1 April 2022
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 17 (4) , e0265929
Open AccessMultiple correspondence analysis as a tool for examining Nobel Prize data from 1901 to 2018
The main goal of this paper is to examine Nobel Prize data by studying the association among the laureate’s country of birth or residence, discipline, time period in which the Nobel Prize was awarded, and gender of the recipient. Multiple correspondence analysis is used as a tool to examine the association between these four categorical variables by cross classifying them in the form of a four-way contingency table. The data that we examine comprise Nobel Prize recipients from 1901 to 2018 (inclusive) from eight-developed countries, with a total sample of 785 Nobel Prize recipients. The countries include Canada, France, Germany, Italy, Japan, Russia, the British Isles, and the USA and the disciplines in which the individuals were awarded the prizes include chemistry, physics, physiology or medicine, literature, economics, and peace.