Variation talk: Articulating meaning in statistics

Little is known about the way that teachers articulate notions of variation in their own words. The study reported here was conducted with 17 prospective secondary math and science teachers enrolled in a preservice teacher education course which engaged them in statistical inquiry of testing data. This qualitative study examines how these preservice teachers articulated notions of variation as they compared two distributions. Although the teachers made use of tandard statistical language, they also expressed rich views of variation through nonstandard terminology. This paper details the statistical language used by the rospective teachers, categorizing both standard and nonstandard expressions. Their nonstandard language revealed strong relationships between expressions of variation and expressions of distribution. Implications and the benefits of nonstandard language in statistics are outlined.

Equational Reasoning as a Tool for Data Analysis

A combination of deductive reasoning, clustering, and inductive learning is given as an example of a hybrid system for exploratory data analysis. Visualization is replaced by a dialogue with the data.

Parameter setting and statistical learning

Three main models of parameter setting have been proposed: the Variational model proposed by Yang (2002; 2004), the Structured Acquisition model endorsed by Baker (2001; 2005), and the Very Early Parameter Setting (VEPS) model advanced by Wexler (1998). The VEPS model contends that parameters are set early. The Variational model supposes that children employ statistical learning mechanisms to decide among competing parameter values, so this model anticipates delays in parameter setting when critical input is sparse, and gradual setting of parameters. On the Structured Acquisition model, delays occur because parameters form a hierarchy, with higher-level parameters set before lower-level parameters. Assuming that children freely choose the initial value, children sometimes will miss-set parameters. However when that happens, the input is expected to trigger a precipitous rise in one parameter value and a corresponding decline in the other value. We will point to the kind of child language data that is needed in order to adjudicate among these competing models.

Mortality variation across Australia: descriptive data for States and Territories, and statistical divisions

OBJECTIVE: To describe variation in all cause and selected cause-specific mortality rates across Australia. METHODS: Mortality and population data for 1997 were obtained from the Australian Bureau of Statistics. All cause and selected cause-specific mortality rates were calculated and directly standardised to the 1997 Australian population in 5-year age groups. Selected major causes of death included cancer, coronary artery disease, cerebrovascular disease, diabetes, accidents and suicide. Rates are reported by statistical division, and State and Territory. RESULTS: All cause age-standardised mortality was 6.98 per 1000 in 1997 and this varied 2-fold from a low in the statistical division of Pilbara, Western Australia (5.78, 95% confidence interval 5.06-6.56), to a high in Northern Territory-excluding Darwin (11.30, 10.67-11.98). Similar mortality variation (all p<0.0001) exists for cancer (1.01-2.23 per 1000) and coronary artery disease (0.99-2.23 per 1000), the two biggest killers. Larger variation (all p<0.0001) exists for cerebrovascular disease (0.7-11.8 per 10,000), diabetes (0.7-6.9 per 10,000), accidents (1.7-7.2 per 10,000) and suicide (0.6-3.8 per 10,000). Less marked variation was observed when analysed by State and Territory. but Northern Territory consistently has the highest age-standardised mortality rates. CONCLUSIONS: Analysed by statistical division, substantial mortality gradients exist across Australia, suggesting an inequitable distribution of the determinants of health. Further research is required to better understand this heterogeneity.

Statistical questions - Comment

No Abstract

Applying statistical approaches in the dissection of genes versus environment for asthma and allergic disease

Now that some of the genes involved in asthma and allergy have been identified, interest is turning to how genetic predisposition interacts with exposure to environmental risk factors. These questions are best answered by studies in which both genotypes and other risk factors are measured, but even simpler studies, in which family history is used as a proxy for genotype, have made suggestive findings. For example, early breast feeding may increase the risk of allergic disease in genetically susceptible children, and decrease the risk of 'sporadic' allergy. This review also addresses the overall importance of genetic causes of allergic disease in the general population.

Solicitors disciplinary hearings in Queensland 1930-2000: a statistical analysis

This article reports on the results of a study undertaken by the author together with her research assistant, Heather Green. The study collected and analysed data from all disciplinary tribunal decisions heard in Queensland since 1930 in an attempt to provide empirical information which has previously been lacking. This article will outline the main features of the disciplinary system in Queensland, describe the research methodology used in the present study and then report on some findings from the study. Reported findings include a profile of solicitors who have appeared before a disciplinary hearing, the types of matters which have attracted formal discipline and the types of orders made by the tribunal. Much of the data is then presented on a time scale so as to reveal any changes over time.