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How does a statistical model differ from a mathematical model? What
are the differences among the sample distribution, the sampling
distribution, and the population distribution? In an experiment,
what effect does the sampling method have on the results? What are
the implications of the use of processes of random selection and
random assignment? Can a small sample yield accurate estimates of
population parameters? This book examines five big ideas and
twenty-four related essential understandings for teaching
statistics in grades 9–12. The authors distinguish mathematical
and statistical models, explore distributions as descriptions of
variability in data, focus on the fundamentals of testing
hypotheses to draw conclusions from data, highlight the importance
of the data collection method, and recognise the need to examine
bias, precision, and sampling method in evaluating statistical
estimators. Recognising that analysing data is an important part of
understanding the world, the authors discuss the growth of
students’ ideas about statistics and examine challenges to
teaching, learning, and assessment. They intersperse their
discussion with questions for teachers’ reflection.
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