Literature Index

Displaying 2191 - 2200 of 3326

  • Statistically, Technologically, and Contextually Provocative Tasks: Supporting Teachers' Informal Inferential Reasoning

    Author(s):
    Sandra R. Madden
    Editors:
    1
    Year:
    2011
    Abstract:
    Recent studies have highlighted the potential importance of informal inferential reasoning (IIR) in supporting learners' general statistical reasoning. This paper presents a framework based on a retrospective analysis of design research in the context of technology-rich statistical professional learning experiences for high school mathematics teachers. The framework was developed to understand elements of the tasks - identified as statistically, contextually, and/or technologically provocative - that appeared to trigger the teachers' engagement and IIR. Characteristics that make a task provocative and how tasks may interact to impact learning are explored and connected to theories including expectation failure and epistemological obstacles.
    Location:
    http://www.informaworld.com/smpp/title~db=all~content=g932654185

  • Statistication: The quest for a curriculum

    Author(s):
    Zidek, J. V.
    Editors:
    Davidson, R., & Swift, J.
    Year:
    1986
    Abstract:
    I want to take this opportunity to speak about the special problems we statistical educators face in trying to develop a suitable curriculum for statistics instruction. I will argue that we are far from successful. I will emphasize ways in which statistics is different qualitatively from other subjects in this regard.

  • Statistics - Driving Success Or Blocking The Road?

    Author(s):
    Zayac, S. A.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    Yes, and yes. Success is dependent on developing conceptual understanding, easing interpretation, simplifying validation and facilitating corrective action. Focusing on statistical theory, data manipulation and increasing mathematical sophistication blocks the road to improvement. Lessons, learned over the past quarter century, in instructional strategies, in defining learning objectives and in using interactive examples, will be reviewed. Experience, demonstrating that developing EDA, measurement, DOE, prediction and control skills are critical, will be shared. Driven by the paradigm of statistical thinking and the concepts of quantitative literacy, compatible with the philosophies of Deming, Juran and Box, these approaches can ease implementation of ISO standards and accelerate the effectiveness of Six Sigma technologies.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/1/4g1_zaya.pdf

  • Statistics - Keeping it in the women's world

    Author(s):
    Clark, M.
    Editors:
    Vere-Jones, D., Carlyle, S., & Dawkins, B. P.
    Year:
    1991
    Abstract:
    In the secondary schools, statistics, above other branches of mathematics, is proving attractive to female students. What happens then when this substantial proportion of young women come to university - do they continue to study statistics and do they succeed at it?

  • Statistics 105 - Real-Life Statistics: Your Chance for Happiness (or Misery)

    Author(s):
    Xiao-Li Meng, with Yves Chretien, Paul Edlefsen, Kari Lock, and Cassandra Wolos
    Year:
    2008
    Abstract:
    Statistics 105 is a team-designed course that has received local media attention (e.g., www.news.harvard.edu/gazette/2008/02.14/11-stats.html). Its course description promises the following:<br><br>Discover an appreciation of statistical principles and reasoning via "Real-Life Modules" that can make you rich or poor (financial investments), loved or lonely (on-line dating), healthy or ill (clinical trials), satisfied or frustrated (chocolate/wine tasting) and more. Guaranteed to bring happiness (or misery) both to students who have never taken a previous statistics course, and to those who have taken statistics and want to see how statistical thinking applies to so many areas of life.<br><br>This webinar will reveal its history, pedagogical motivation, innovations, and challenges along the way.
    Location:
    http://www.causeweb.org/webinar/2008-11/

  • Statistics achievement: A function of attitudes and related experiences

    Author(s):
    Elmore, P. B, Lewis, E. L., &amp; Bay, M. L. G.
    Year:
    1993
    Abstract:
    The effects of previous mathematics, statistics, and computer science coursework; attitudes toward statistics and computers; and mathematics ability on statistics achievement were studied for 289 college students over four semesters. A secondary purpose of the study was to determine the effect of the computer laboratory component of an inferential statistics class on students' end of course attitudes. No statistically significant differences were found between students taught with a computer laboratory and those taught without the computer component for attitudes toward statistics, but those taught by computer exhibited more positive attitudes toward the computer and less statistical anxiety at the end of the course.

  • Statistics and computer attitudes and achievement of students enrolled in applied statistics: Effect of a computer laboratory

    Author(s):
    Elmore, P. B., &amp; Lewis, E. L.
    Year:
    1991
    Abstract:
    This study was conducted to determine the effect of previous mathematics, statistics, and computer science coursework; attitudes toward statistics and computers; and mathematics ability on statistics achievement. A secondary purpose of this study was to determine the effect of the computer laboratory component of an inferential statistics class on the end of course attitudes toward statistics and computers controlling for precourse attitudes.

  • Statistics and data analysis at Grade 6-8: What middle grades students need to know and be able to do

    Author(s):
    Friel, S. N., &amp; O'Connor, W.

  • Statistics and finance: Living on the "hedge".

    Author(s):
    Gimeno, R., &amp; Mateos de Cabo, R.
    Editors:
    Rossman, A., &amp; Chance, B.
    Year:
    2006
    Abstract:
    Statistics plays a leading role in finance. The explosive development of increasingly complex markets makes it more and more difficult for practitioners to correctly value financial asset. Statistical analysis has become a powerful tool for a better market valuation, taking a leading role in the development of new financial products that try to hedge the increasing amount of risks that an investor has to take. Statistics knowledge demand is steadily increasing in Hedge Funds, Investment Banking and Financial Institutions in general, where statistics students could developed a professional career. Finance can be seen as a way to motivate students on the applications of almost any statistical tool we would like to teach them, since we could always find an example where these techniques are put into practice.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/17/5G2_GIME.pdf

  • Statistics and mathematics anxiety in social science students: Some interesting parallels

    Author(s):
    Zeidner, M.
    Year:
    1991
    Abstract:
    This study illuminates some interesting parallels between statistics anxiety and mathematics anxiety in social science students. Parallel to what is confirmed for mathematics anxiety, two factors were observed to underly statistics anxiety scores, namely, statistics test anxiety and content anxiety. The study revealed modest though significant correlations between student attributes and the two confirmed dimensions of statistics anxiety. Furthermore, parallel to the inverse correlation reported for mathematics anxiety and math course performance, statistics anxiety correlated negatively with high school matriculation scores in math as well as self perceptions of math abilities. These data lend support to the hypothesis that aversive prior experiences with mathematics, prior poor achievement in math, and a low sense of math self-efficacy are meaningful antecedent correlates of statistics anxiety and thus lend some credence to the "deficit" interpretation of statistics anxiety.

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The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education