Literature Index

Displaying 221 - 230 of 3326

  • A web environment to improve connections between mathematics and statistics learning.

    Author(s):
    Mignani, S., Monari, P., Ricci, R., & Orlandoni, A.
    Editors:
    Rossman, A., & Chance, B.
    Year:
    2006
    Abstract:
    The paper describes a project involving cooperative learning of statistical topics implemented in a web environment. The project is the result of a fruitful partnership between the Faculty of Statistics of the University of Bologna and the Institute of Educational Research of the Emilia Romagna Region. The synergy between mathematics and statistics offers a concrete example of theoretical method application in order to investigate the real world. The positive effects of cooperative learning can be broadened to a larger learning-teaching community. It makes it possible to create a virtual place where it is possible to realize a cooperative learning milieu. This methodology is particularly useful for statistics, given both the specificity of the discipline and the fact that teaching of the subject often represents a novelty for mathematics teachers. Problems connected with real life are presented on the web and project participants may communicate through the network.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/17/1C3_MIGN.pdf

  • A Web Site That Provides Resources for Assessing Students' Statistical Literacy, Reasoning and Thinking

    Author(s):
    Joan Garfield, Robert delMas
    Year:
    2010
    Abstract:
    The Assessment Resource Tools for Improving Statistical Thinking (ARTIST) Web site was developed to provide high-quality assessment resources for faculty who teach statistics at the tertiary level but resources are also useful to statistics teachers at the secondary level. This article describes some of the numerous ARTIST resources and suggests ways teachers may use these assessment resources.
    Location:
    http://www3.interscience.wiley.com/journal/123238050/abstract

  • A Website Containing Information On Statistical Textbooks

    Author(s):
    Mckenzie, J. D.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    This paper describes a website containing information on textbooks for the introductory, applied statistics course. After an explanation of the rationale for such a site it lists the general education and business and economics textbooks on the site followed by characteristics of each text on the site. It concludes with future possibilities for such a site.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/1/10_13_mc.pdf

  • A whole lotto education!

    Author(s):
    Lesser, L. M.
    Year:
    2003
    Abstract:
    ) Describes classroom explorations of the interpretation and calculation of probabilities involved in a representative state lottery. TI-83 calculator commands are given for simulating drawings as well as for calculating relevant probabilities using the binomial, geometric, Poisson, and other distributions.
    Location:
    http://www.tenet.edu/tctm/downloads/journal_fall03.pdf

  • A'Striking' Demonstration of the Poisson Distribution.

    Author(s):
    Buonaccorsi, V. & Skibiel, A.
    Editors:
    Goodall, G.
    Year:
    2005
    Abstract:
    This article describes a simple classroom activity that helps students immediately visualize and understand the meaning and mathematical properties of the Poisson distribution.

  • About the meaning of the data: Ueber eine Bedeutung von Daten

    Editors:
    Chieppa, M.
    Year:
    1986
    Abstract:
    Generally, when empirical statistical distributions are discussed in basic text books, a stress is given to the type of the data (quantitative, qualitative, ..). Rarely the problem of the meaning of the data and of their quality is treated. Only in the text books of sampling techniques and in some books of applied statistics this problem is considered, essentially with reference to the collection of the data. We think, instead, that it is very important to explain also the meaning of the data and the fact that they are one of the possible images of the phenomena. A summarized exposition of the problem is presented, emphasizing some particular aspects. (orig.)

  • Academic versus applied training in statistics: Approach used by the U.S. Bureau of the Census

    Author(s):
    Shoemaker, H. H., Bryson, K. R., Brown, P., & Solomon, L.
    Editors:
    Davidson, R., & Swift, J.
    Year:
    1986
    Abstract:
    The goal of ISPC training program (both international and domestic) has been, and will continue to be to promote personal and organizational statistical development by equipping statisticians and data processing specialists with the practical skills and conceptual background to enable them to adapt the latest technologies to the circumstances and needs of their countries or organizations. As the development needs of members of the world statistical community change, as new technologies emerge, and as new instructional methods become feasible, the ISPC training programs must continue to adapt to these challenges and opportunities.

  • Accepting the null hypothesis

    Author(s):
    Frick, R. W.
    Year:
    1995
    Abstract:
    This article concerns acceptance of the null hypothesis that one variable has no effect on another. Despite frequent opinions to the contrary, this null hypothesis can be correct in some situations. Appropriate criteria for accepting the null hypothesis are (1) that the null hypothesis is possible; (2) that the results are consistent with the null hypothesis; and (3) that the experiment was a good effort to find an effect. These criteria are consistent with the meta-rules for psychology. The good-effort criterion is subjective, which is somewhat undesirable, but the alternative--never accepting the null hypothesis--is neither desirable nor practical.

  • Accessible Methodologies For Estimating Density Functions

    Author(s):
    Provost, S. B.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    It is often the case that the moments of a distribution can be readily determined, while its exact density function is mathematically intractable. We show that the density function of a continuous distribution defined on a closed interval can be easily approximated from its exact moments by solving a linear system involving a Hilbert matrix. When sample moments are being used, the same linear system will yield density estimates. A simple formula that is based on an explicit representation of the elements of the inverse of a Hilbert matrix is being proposed as a means of directly determining density estimates or approximants without having to resort to kernels or orthogonal polynomials. As illustrations, density estimates will be determined for the 'Buffalo snowfall' data set and the density of the distance between two random points in a cube will be approximated. Finally, an alternate methodology is proposed for obtaining smooth density estimates from averaged shifted histograms.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/1/3b3_prov.pdf

  • Accounting for teachers' instructional realities when supporting their professional development in statistics.

    Author(s):
    Cortina, J. L., Zhao, Q., & Visnovská, J.
    Editors:
    Rossman, A., & Chance, B.
    Year:
    2006
    Abstract:
    In this paper we analyze a design experiment aimed at supporting the professional development in statistics of twelve middle-school teachers in the United States. We explain how adopting a sociocultural framework allowed us to account for teachers' struggles to make sense of instructional practices in statistics that place students' reasoning at the center of instructional decision-making. We also account for how the adoption of the sociocultural framework allowed us to envision a viable way in which to better support the professional development of the participating teachers.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/17/2G2_CORT.pdf

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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