Statistical modelling of road accident data via graphical models and hierarchical Bayesian models.

The objective of this thesis is to develop statistical models for multivariate road accident data. Two directions of research are followed: graphical modelling for contingency tables cross-classified by accident characteristics, and hierarchical Bayesian models for multiple accident frequencies of different types modelled jointly. Multi-dimensional tables are analysed and it is shown how to use collapsibility to reduce the dimensionality of the analysis without the problems of Simpson's paradox. It is revealed that accident severity and the number of casualties are associated, and that these variables are mainly influenced by the number of vehicles and speed limit. Graphical chain models allow causal hypotheses to be formulated and it is shown how they are valuable tools for empirical research about road accident characteristics. The hierarchical Bayesian models developed combine generalized linear models with random effects. The novelty of these models consists in the joint modelling of multiple response variables. The models account for overdispersion and they are used for accident prediction and for ranking hazardous sites. All models are fully Bayesian and are fitted using Markov Chain Monte Carlo methods. It is shown that multiple response variables models are superior to separate univariate response models. Some theoretical problems are examined regarding the maximum likelihood estimation process for the two parameters negative binomial distribution. A condition is given that is equivalent with unique maximum likelihood estimators. The two directions of research are connected by using graphs to describe the models. In addition, a new Bayesian model selection procedure for contingency tables is proposed. This is based on Gibbs sampling and avoids problems associated with asymptotic tests. The conclusions revealed here can help practitioners to design better safety policies and to spend money more wisely on sites that really are dangerous

Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report 2016

In 2005 the American Statistical Association (ASA) endorsed the Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report. This report has had a profound impact on the teaching of introductory statistics in two- and four-year institutions, and the six recommendations put forward in the report have stood the test of time. Much has happened within the statistics education community and beyond in the intervening 10 years, making it critical to re-evaluate and update this important report. For readers who are unfamiliar with the original GAISE College Report or who are new to the statistics education community, the full version of the 2005 report can be found at http://www.amstat.org/education/gaise/GaiseCollege_full.pdf and a brief history of statistics education can be found in Appendix A of this new report. The revised GAISE College Report takes into account the many changes in the world of statistics education and statistical practice since 2005 and suggests a direction for the future of introductory statistics courses. Our work has been informed by outreach to the statistics education community and by reference to the statistics education literature

The Gene Ontology Handbook

bioinformatics; biotechnolog

The emotional influences on vendors' residential price perception (The price virus)

The aim of this study is to explore what causes the gap between the asking price and the buying price of houses in Australia. According to 2012 statistics provided by Real Estate Institute of Western Australia, home sales records shows approximately 70 per cent of the homes listed for sale did not achieve their asking price. The research hypothesis adopted in this thesis is that this gap is caused by vendors’ emotional attachment to the home, which in turn influences an unrealistic price. The proposal of this unrealistic price is the focus of the research investigation. The objective is to explore the hypothesis that home vendors are socially and emotionally conditioned to perceive their home to be worth more than its actual market value. The effect of irrational behaviour influenced by vendors’ emotions is deemed to be linked to their unrealistic perception of price. Home ownership is a key sector of the property industry, now Australia’s biggest industry, larger even than mining. The industry contributed $185.5 billion to the economy, equivalent to 11.5 per cent of GDP in the last financial year. The latest data shows that Australian homes are currently worth$5.0 to $5.5 trillion dollars. Depending on the source, the estimate for number of residential properties sold each year in Australia is between 400,000 and 600,000. If indeed unrealistic price perception is influenced by human emotions in an industry as big as this, then there are cogent reasons for exploring this phenomenon. This study employed a questionnaire survey relating to the research question. The survey was hosted on Fairfax Media’s websites and received responses from all over Australia as well as 11 other countries. The participants in the survey were mainly homeowners who had sold or had attempted to sell their homes, which enabled this study to explore the emotional behaviour underlying how homeowners arrive at a value for their homes. Five emotions were assessed as key variables that affect price perception across the emotional stages in decision-making. The results suggests that the strongest factor influencing unrealistic price perception is greed, followed by vendors’ expectation that buyers will negotiate, a lack of trust in the real estate agent and pride in ownership. The findings reveal that the feeling of uniqueness of the home also influences this unrealistic price perception. It is hoped that this study will contribute to the real estate industry by providing a better insight into why vendors tend to overprice their homes. The results of this research could therefore provide an improved understanding of home vendors’ behaviour, and offer an important insight into the implications of emotional attachment in relation to decision-making and the perceived value of the home

Pollination networks: dynamic responses to rain-driven resource pulses

Pollination is essential to life on earth. The network of species interactions within a plant-pollinator community exhibit structures which support species coexistence and the persistence of pollination. My thesis centers on understanding how network structure and function respond to rain-driven resource pulses. I sampled a spatially and temporally resolved set of 18 flower-visitation networks in the Simpson Desert, Australia, and discovered 33 new bee species. To ensure representative sampling of pollinators, I compared net sampling and pan trapping. Net sampling more effectively captured visitor diversity and abundance, reflected the spatio-temporal variability in floral resources, and linked visitors to pollination through behavioural observations. I next tested if visitation networks are adequate substitutes for pollination networks. Networks were similar in structure, but the pollen-transport network displayed higher specialisation, lower interaction evenness and fewer links, and pollen transport was confirmed in only one third of visitation interactions. I then tested how rain affected community and network structure. Species diversity and composition varied dramatically with rainfall. An increase in the previous nine months cumulative rainfall increased network size and specialisation, but when network size was accounted for, nestedness and connectance were unaffected. Networks changed in distinct ways: plant species richness determined the number of modules, the richness of poorly connected visitor species determined module size, and the number of well-connected species per module was never greater than one. Finally, I tested if species traits determined a species network role, and found zygomorphic plant species became more connected as bee species richness increased, suggesting species complementarity. My thesis demonstrated that pollination is ensured through stable network structure, despite rain-driven changes in network makeup and species network role

Patterns of Foraminiferal Micro-evolution and Enviromental Change in the Lower Chalk

The research tests Sheldon's Plus ҫa change model by tracking a single fossil lineage through a succession of marine environments showing geological-scale differences in background stability. Orbitally driven cyclic sediments of Cenomanian age, predominantly recording a 20 kyr precessional shift, provide both the time-frame and the main engine of environmental variability, although transgressive pulses and other events are also superimposed. The cyclicity provides spectacular geographical and temporal control,, allowing a million-year sequence to be sampled at 100 kyr intervals at three laterally adjacent sites, and partially sampled at 20 kyr and 2 kyr intervals at one of these sites. The lineage of interest is a benthic agglutinated foraminiferan, Tritaxia pyramidata, which occurs in prolific numbers; additional ecological evidence comes from a large microfossil database recovered from the same samples. The Lower Chalk benthic microfauna have very stable patterns of relative abundance, with the same species occurring in similar proportions for at least a million years. Analysis of Tritaxia's ecology identifies it as an r-selected generalist playing a keystone role in the community. During development, Tritaxia exhibits a persistent tendency to uncoil, but this tendency is strongly manifest only after average life expectancy, leading to its interpretation as a construction mistake rather than a product of design. This developmental quirk sheds light on the grain and texture of the morphospace through which Tritaxia is forced to navigate, significantly limiting its evolutionary potential. The result is a lineage that achieves a million years' worth of wobbly stasis, largely because it is boxed into a small corner of morphospace by the joint influence of a narrow developmental channel and competitive interference from other species. The dynamics, of this process predominantly support the Plus ҫa change model, even though not all the predicted patterns are found