Scientific Reasoning Research Institute - informal statistical inference en Konold et al. (2011) <div class="pub-title">Conceptual challenges in coordinating theoretical and data-centered estimates of probability</div> <div class="pub-authors">Konold, C. <br />Madden, S. <br />Pollatsek, A. <br />Pfannkuck, M. <br />Wild, C. <br />Ziedins, I. <br />Finzer, W. <br />Horton, N. J. <br />Kazak, S. </div> <div class="pub-year">(2011)</div> <div class="pub-citation"><p><i>Mathematical Thinking and Learning</i>, 13, 68-86.</p> </div> <div class="pub-abstract"> <p>A core component of informal statistical inference is the recognition that judgments based on sample data are inherently uncertain. This implies that instruction aimed at developing informal inference needs to foster basic probabilistic reasoning. In this article, we analyze and critique the now-common practice of introducing students to both “theoretical” and “experimental” probability, typically with the hope that students will come to see the latter as converging on the former as the number of observations grows. On the surface of it, this approach would seem to fit well with objectives in teaching informal inference. However, our in-depth analysis of one eighth-grader’s reasoning about experimental and theoretical probabilities points to various pitfalls in this approach. We offer tentative recommendations about how some of these issues might be addressed.</p> </div> <table id="attachments" class="sticky-enabled"> <thead><tr><th>Attachment</th><th>Size</th> </tr></thead> <tbody> <tr class="odd"><td><a href=" et al. (2011).pdf">Konold et al. (2011).pdf</a></td><td>384.94 KB</td> </tr> </tbody> </table> Experimental probability informal inferential reasoning informal statistical inference Law of Large Numbers probability instruction probability simulation theoretical probability true probability Sat, 07 May 2011 02:43:33 +0000 konold 503 at