The two key issues of modern Bayesian statistics are: (i) establishing principled approach for distilling statistical prior that is consistent with the given data from an initial believable scientific prior; and (ii) development of a consolidated Bayes-frequentist data analysis workflow that is more effective than either of the two separately. In this paper, we propose the idea of “Bayes via goodness-of-fit” as a framework for exploring these fundamental questions, in a way that is general enough to embrace almost all of the familiar probability models. Several examples, spanning application areas such as clinical trials, metrology, insurance, medicine, and ecology show the unique benefit of this new point of view as a practical data science tool.

Data collected in many biology laboratory classes are on ratio or interval scales where the size interval between adjacent units on the scale is constant, which is a critical requirement for analysis with parametric statistics such as t-tests or analysis of variance. In other cases, such as ratings of disease or behavior, data are collected on ordinal scales in which observations are placed in a sequence but the intervals between adjacent observations are not necessarily equal. These data can only be interpreted in terms of their order, not in terms of the differences between adjacent points. They are unsuitable for parametric statistical analyses and require a rank-based approach using nonparametric statistics. We describe an application of one such approach, the Kruskal-Wallis test, to biological data using online freeware suitable for classroom settings.

The peer-reviewed Australian Zoologist, first published in 1914, is Australia’s longest-lived zoological journal. Its publication history shows changes in the zoological topics covered over the last 100 years, including the animals studied, characteristics of the authors and readership, and the influence of the databases used to study the journal on information retrieval. Searches in different databases retrieved different numbers of papers; Scopus (including secondary documents not in the database but cited by documents that are in the database) was the most comprehensive. Although authors from 22 countries contributed papers over the history of the Australian Zoologist, over 90% of authors were Australian. Most international authors came from the USA, the UK, Canada and New Zealand. Approximately two-thirds of authors citing Australian Zoologist were Australian-based, but there were still 10 or more authors from each of thirty-four other countries citing Australian Zoologist: while regional, the journal has an international profile. Highly cited papers in Australian Zoologist had high mean Scopus percentile ranks (20th century 83.9, 21st century 73.7), indicating that in comparison to their fields globally, these papers are used well above average. Considering all papers published in Australian Zoologist, over time the proportion of papers in the categories ‘Biodiversity & Conservation’ and ‘Environmental Sciences & Ecology’ rose significantly, reflecting the increased research in these areas. Between 2013 and 2019, when relevant metrics are available in Scopus, Australian Zoologist declined in no metric measured while improving significantly in CiteScore, Highest Percentile, and % Cited, indicating increasing references to Australian Zoologist papers by other peer-reviewed publications. Between 2010 and 2019, 2.1% of Australian Zoologist papers were ranked within the top 10% in their fields globally, based on citation impact. Authors considering publishing in Australian Zoologist should note that longer papers are acceptable, colour imagery (including photographs) is encouraged, the journal is visible in major databases, it is cited internationally and there are no page charges.

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