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Past research on gambling behavior has focused largely on cognitive and affective explanations, but has not explored the influence of past gambling behavior or habit. In this study, it was hypothesized that gambling behavior followed predictable patterns based on past behavior. We found that these patterns could be described by the negative binomial distribution (NBD) and NBD–Dirichlet models at game and category levels, respectively. An empirical study using the 1999 Australia Productivity Commission survey dataset provided some support for the usefulness of these models in describing gambling consumption. The paper explores the implications for identifying problem gambling and influencing gamblers’ behavior. [ABSTRACT FROM AUTHOR]

Summary This paper uses a new bivariate negative binomial distribution to model scores in the 1996 Australian Rugby League competition. First, scores are modelled using the home ground advantage but ignoring the actual teams playing. Then a bivariate negative binomial regression model is introduced that takes into account the offensive and defensive capacities of each team. Finally, the 1996 season is simulated using the latter model to determine whether or not Manly did indeed deserve to win the competition. [ABSTRACT FROM AUTHOR]

The beta-binomial distribution is used to provide estimates of the probability of detecting a rare species, the smallest proportion cover detectable with a stated confidence for a survey, and is a method for estimating the sample size required to detect a species with a stated presence at a stated level of confidence for independent clusters of binary data. The equations, while general were derived in the context of marine benthic video transects and are useful for evaluating a wide range of existing surveys or designing new surveys. Application of the equations is demonstrated for a data set collected from three marine surveys on the Great Barrier Reef in Australia. [ABSTRACT FROM AUTHOR]