Literature Index

Displaying 2881 - 2890 of 3326

  • The Separation Principle in Linear Regression

    Author(s):
    Samaniego, F. J., & Watnik, M. R.
    Year:
    1997
    Abstract:
    In linear regression problems in which an independent variable is a total of two or more characteristics of interest, it may be possible to improve the fit of a regression equation substantially by regressing against one of two separate components of this sum rather than the sum itself. As motivation for this "separation principle," we provide necessary and sufficient conditions for an increased coefficient of determination. In teaching regression analysis, one might use an example such as the one contained herein, in which the number of wins of Major League Baseball teams is regressed against team payrolls, for the purpose of demonstrating that an investigator can often exploit intuition and/or subject-matter expertise to identify an efficacious separation.
    Location:
    http://www.amstat.org/publications/jse/v5n3/samaniego.html

  • The simulation heuristic

    Author(s):
    Kahneman, D., & Tversky, A.
    Editors:
    Kahneman, D., Slovic, P., & Tversky, A.
    Year:
    1982
    Abstract:
    We shall argue that assessments of propensity and probability derived from mental simulations are used in several tasks of judgment and also that they play a significant role in several affective states. We first list some judgmental activities in which mental simulation appears to be involved. We then describe a study of the cognitive rules that govern the mental undoing of past events, and we briefly discuss the implications of these rules for emotions that arise when reality is compared with a favored alternative, which one had failed to reach but could easily imagine reaching. We conclude this brief sketch of the simulation heuristic by some remarks on scenarios, and on the biases that are likely to arise when this heuristic is used.

  • The Standard Deviation: Some Drawbacks of an Intuitive Approach

    Author(s):
    Loosen, F., Lioen, M., & Lacante, M.
    Year:
    1985
    Abstract:
    In a recent issue of this journal, Hart [2] mentioned that "she made a habit of asking students of all levels what a standard deviation is". She complained that in most students the only answer was: "It's a measure of spread", upon which they provide a formula. We are still more pessimistic. We doubt whether most students do realize that the standard deviation is a special measure of spread: one that measures how strongly the data depart from central tendency. Our doubt has been induced by the way in which many textbooks introduce the concept of variability. Most introductions put a stronger emphasis on the heterogeneity among the observations than on their deviations from the central tendency. An example may illustrate our point.

  • The standards applied: Teaching data visualization

    Author(s):
    Van Reeuwijk
    Year:
    1992
    Abstract:
    As part of the project Design, Development and Assessment in Mathematics Education, I spent four weeks at Whitnall High School in Milwaukee, Wisconsin, testing a booklet on descriptive statistics called Data Visualization.

  • The statistical education of grades Pre-K-2 teachers: A shared responsibility.

    Author(s):
    Franklin, C. A., & Mewborn, D. S.
    Editors:
    Burrill, G. F.
    Year:
    2006
    Abstract:
    This article describes a collaborative effort at the university level between statisticians and mathematics educators as well as two initiatives of the American Statistical Association (ASA): Statistics Teacher Education: Assessment, Methods, Strategies (TEAMS) conference, and Guidelines in Assessment and Instruction for Statistical Education (GAISE).

  • THE STATISTICAL PERFORMANCE IN A COMPARATIVE STUDY BETWEEN CENTRAL AMERICAN TEACHERS

    Author(s):
    M. Alejandra Sorto
    Year:
    2008
    Abstract:
    The statistical performance on an instrument used to compare teachers' knowledge in two Central American countries is examined. The hypothesis is that there are differences in the performance of statistics items given that one country has a higher allocation of resources for education and higher level of teacher preparation in statistics. A total of 250 third and seventh grade teachers and primary pre-service teachers were surveyed from randomly selected schools in both countries. Results show that there are significant differences between countries for items measuring graphical comprehension and between seventh grade teachers and others for an item measuring statistical concepts in the context of teaching.
    Location:
    http://www.ugr.es/~icmi/iase_study/Files/Contents.htm

  • The Statistical Re-Education Of Psychology

    Author(s):
    Cumming, G., Fidler, F. & Thomason, N.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    Psychology remains addicted to null hypothesis significance testing despite decades of effort by reformers. Extensive changes in statistical understanding and practices are needed. The authors propose a model of reform-the statistical re-education of psychology-by making an analogy with the conceptual change model of learning. Four diverse components of reform are identified, and illustrated by brief examples of research. Reform is especially challenging because many statistics teachers in psychology first need to achieve conceptual change themselves. In relation to a highly desirable increase in use of confidence intervals (CIs), it seems that many psychologists do not understand CIs well, and guidelines for CI use are lacking. The conceptual change model is offered to guide research needed on many aspects of reform, and the important and exciting task of the statistical re-education of psychology.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/1/6c3_cumm.pdf

  • The statistically marvelous medical growth chart: A tool for teaching variability

    Author(s):
    Weaver, K. A.
    Year:
    1999
    Abstract:
    Plotting girls' and boys' weights on a medical growth chart in the introductory statistics course illustrates variability, the normal distribution, percentiles, z scores, outliers, bivariate graphing, and simple regression. The chart presents the spread of weights for newborns through 36 months, includes percentile scores, and represents a bivariate distribution with age on the abscissa and weight on the ordinate. Students plot their own weights to understand how the chart works and then plot the weights of a selected boy and girl to understand how the chart identifies outliers for follow-up tests on hormone levels, nutrition, and intellectual development. Instructors in other psychology courses (e.g., developmental, child, abnormal, introductory, and educational psychology) may also find the chart useful when covering infant development.

  • The statistician and the pedagogical monster: Characteristics of effective instructors of large statistics classes

    Author(s):
    Stroup, D. F.
    Year:
    1984
    Abstract:
    This paper offers suggestions in the areas of enthusiasm, organization and clarity, one-to-one skills, one-to-group skills, and an analytic/synthetic approach to teaching.
    Location:
    RISE

  • The statistics concepts inventory: Developing a valid and reliable instrument

    Author(s):
    Allen, K., Stone, A., Rhoads, T. R., Murphy, T. J.
    Year:
    2004
    Abstract:
    The Statistics Concepts Inventory (SCI) is currently under development at the University of Oklahoma. This paper documents the early stages of assessing the validity, reliability, and discriminatory power of a cognitive assessment instrument for statistics. The evolution of test items on the basis of validity, reliability, and discrimination is included. The instrument has been validated on the basis of content validity through the use of focus groups and faculty surveys. Concurrent validity is measured by correlating SCI scores with course grades. The SCI currently attains concurrent validity for Engineering Statistics courses, but fails to do so for Mathematics Statistics courses. Because the SCI is targeted at Engineering departments, this is a good starting point, but the researchers hope to improve the instrument so that it has applicability across disciplines. The test is shown to be reliable in terms of coefficient alpha for most populations. This paper also describes how specific questions have changed as a result of answer distribution analysis, reliability, discrimination, and focus group comments. Four questions are analyzed in detail: 1) one that was thrown out, 2) one that underwent major revisions, 3) one that required only minor changes, and 4) one that required no changes.

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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