Problem Formulation
Statistical reasoning may be defined as the way people reason with
statistical ideas and make sense of statistical information (Garfield, 2003).
This involves making interpretations based on sets of data, graphical
representations, and statistical summaries. Much of statistical reasoning
combines ideas with data and chance, which leads to making inferences and
interpreting statistical results. Underlying this reasoning is a conceptual
understanding of important ideas, such as distribution, center, spread,
association, uncertainty, randomness, and sampling. Different form traditional
mathematical reasoning which emphasizes abstraction, statistical reasoning
pays more attention to the context or background of the problem. It is not only
an “output” of education, but also a crucial “input” in the process of learning statistics.
Problem Formulation
Statistical reasoning may be defined as the way people reason with
statistical ideas and make sense of statistical information (Garfield, 2003).
This involves making interpretations based on sets of data, graphical
representations, and statistical summaries. Much of statistical reasoning
combines ideas with data and chance, which leads to making inferences and
interpreting statistical results. Underlying this reasoning is a conceptual
understanding of important ideas, such as distribution, center, spread,
association, uncertainty, randomness, and sampling. Different form traditional
mathematical reasoning which emphasizes abstraction, statistical reasoning
pays more attention to the context or background of the problem. It is not only
an “output” of education, but also a crucial “input” in the process of learning statistics.
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