THE CONCEPT OF DISTRIBUTION

By Chris Wild. 2006

109 citations recorded by the source corpus.

This paper is a personal exploration of where the ideas of “distribution” that we are trying to develop in students come from and are leading to, how they fit together, and where they are important and why. We need to have such considerations in the back of our minds when designing learning experiences. The notion of “distribution” as a lens through which statisticians look at the variation in data is developed. I explore the sources of variation in data, empirical versus theoretical distributions, the nature of statistical models, sampling distributions, the conditional nature of distributions used for modelling, and the underpinnings of inference.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/8ab5f5ccd83ecd16cfc9711618d57f99dab905af

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In Statistics and Probability

Citations in the corpus

The Role of Context in Developing Informal Statistical Inferential Reasoning: A Classroom Study (2011, background): “Such reasoning processes draw on, for example, theoretical notions of population distributions (Wild, 2006) and conceptions of sampling variability.”
REASONING ABOUT INFORMAL STATISTICAL INFERENCE: ONE STATISTICIAN’S VIEW (2008, background): “Another complication is summarized by Wild (2006), who writes: “Assessment of ‘significance’ balances three factors—effect size, variability and sample size—in a very complicated way.”
How Students Learn Statistics Revisited: A Current Review of Research on Teaching and Learning Statistics (2007, background): “These studies also point to the need to spend ample time on the topic of distribution as an important, foundational concept in statistics (Wild, 2006).”
Telling Data Stories: Essential Dialogues for Comparative Reasoning (2010, background): “Moreover, there is a big difference between learning to tell a story that is reasonably logical and correct and learning to tell stories in such a way that the act of telling them constantly reinforces the central statistical concepts and networks of concepts that we seek to build (see Forster & Wil”
Towards more accessible conceptions of statistical inference (2011, background): “Regarding sample versus population, the more generally useful conception of the distribution that is generated by a process, rather than population, is probably too subtle for beginners (Wild, 2006).”
Developing Teachers’ Statistical Thinking (2011, background): “According to Wild (2006) distributions are “a fundamental component of statistical reasoning” (p.”