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• W2103710075 abstract "Several issues surround the continuing implementation of the Chance and Data component of the mathematics curriculum in Australia. First is its survival. Second is the question of how far toward formal inference should the curriculum take students (assuming it survives). Third is what contexts are amenable for understanding the concepts in the curriculum. Fourth is what tools are available to save time and assist in the learning process. One of the ways of ensuring survival is to convince decision makers that Chance and Data can be taught and learned successfully. As is probably true of other parts of the mathematics curriculum, there is sometimes a tendency in Chance and Data to focus on small components, without spending time to fit them into the overall picture of handling data to answer questions and draw conclusions. Playing games with dice might be fun but how does the activity lead to answering meaningful questions? Finding the mean of a set of numbers might be good practice in addition and division but what does it convey about the set of numbers and how can it be useful in answering a question? Drawing a graph might create an attractive, colourful picture but what story is told about a data set, its variation and its clusters of values? Statistics is about telling stories and answering questions based on various types of data. For statisticians the questions involve collecting samples from populations and drawing inferences about the latter from the former, usually based on random selection. For school students statistics is likely to be more what Tukey (1977) called exploratory data analysis, perhaps answering questions limited to their own experience on a known population from which a convenience, rather than random, sample is drawn. One of the aims across the middle years of school should be to provide students a pathway for asking questions about populations within which they see themselves as members. This pathway is signposted with the techniques, such as finding middles, drawing representations, and describing variation, which assist in telling stories and answering questions. Associated with these techniques there are now software packages that will ease the computational burden and provide visual representations to make decision making more intuitive than in the past. The packages can change the focus from performing computations to interpreting and explaining. Experiencing this process is part of informal inference, which will lay the foundation for formal inference in later years." @default.
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• W2103710075 date "2008-12-22" @default.
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• W2103710075 title "Building Informal Inference with TinkerPlots in a Measurement Context" @default.
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