Literature Index

Displaying 631 - 640 of 3326
  • Author(s):
    Chance, B. L.
    Year:
    2002
    Abstract:
    This paper focuses on a third arm of statistical development: statistical thinking. After surveying recent definitions of statistical thinking, implications for teaching beginning students (including non-majors) are discussed. Several suggestions are given for direct instruction aimed at developing "habits of mind" for statistical thinking in students. The paper concludes with suggestions for assessing students' ability to think statistically. While these suggestions are primarily aimed at non-majors, many statistics majors would also benefit from further development of these ideas in their undergraduate education.
  • Author(s):
    Curcio, F. R.
    Year:
    1987
    Abstract:
    In this study, the schema-theoretic perspective of understanding general discourse was extended to include graph comprehension. Fourth graders (n = 204) and seventh graders (n = 185) were given a prior-knowledge inventory, a graph test, and the SRA Reading and Mathematics Achievement Tests during four testing sessions. The unique predictors of graph comprehension for Grade 4 included reading achievement, mathematics achievement, and prior knowledge of the topic, mathematical content, and form of the graph. The unique predictors for Grade 7 were the same except that prior knowledge of topic and graphical form were not included. The results suggest that children should be involved in graphing activities to build and expand relevant schemata needed for comprehension,
  • Author(s):
    EARLEY, Mark A.
    Year:
    2007
    Abstract:
    Creating assessments for introductory statistics courses is not easy, particularly when the goal is to evaluate students' conceptual understanding of statistical concepts. "Understanding" is difficult to measure, but we do know it involves more than just memorization of facts or blindly carrying out mechanical data analysis procedures. This paper presents a framework for developing an assessment system in introductory statistics culminating in a series of comprehensive writing assessments that evaluate students' understandings of larger statistical concepts such as distribution and variability. The purpose of this paper is to help current and future instructors evaluate the assessment systems of their courses, where students are typically most concerned. I will discuss essays on two topics (distribution and variability) from my own introductory statistics course. In these essays, students reflect upon what they have learned, explain it to someone else, and generate examples to support their explanations. This discussion includes how I developed the assessment, how I incorporate it into the overall course structure, and student reactions to the assessment. Excerpts from over 300 student essays highlight (a) how the students reveal their conceptual understandings through writing,<br>(b) common misunderstandings that emerge, and (c) ways I have adapted my course to better develop students' understandings of these concepts.
  • Author(s):
    Fernandez, F., Monroy, O. L., &amp; Rodriguez, L.
    Year:
    1997
    Abstract:
    The authors (teachers-researcher) carried out an exploratory study in which they designed , on the basis of a didactic analysis similar to the one proposed by Vallecillos (1996), three problems of hypothesis tests. Our purpose was to analyze the effects of graphic calculators use in the application and understanding of the concepts of p-value and significance level in the solving of these problems. The study was done with students of a statistics course for Social Sciences at the university level.<br>We studied, on the basis of the problem solving activities done by the students, their errors and difficulties concerning the concepts of significance lebel and p-value. We thought that the graphic calculator use was going to promote the use of the graphic and numeric representations. However, we found that the graphic calculator was used only in order to represent the p-value numeric representation. Even though each student "seems to understand" the concepts of p-value or significance level because he or she can resolve a problem, we find that little changes in data, (i.e., change in test laterality), generate new errors.<br>This result and other similar ones suggest the need to reflect about the phenomena that put into play the concepts in question, the kind of diactical activities that are designed and used in order to work with these concepts, and the conceptions and obstacles which are behind the errors made by the students.
  • Author(s):
    Bear, G.
    Year:
    1995
    Abstract:
    Computationally intensive methods of statistical inference do not fit the current canon of pedagogy in statistics. Seven pedagogical principles are proposed to accommodate those methods and the logic underlying them. These include defining inferential statistics as techniques for reckoning with chance; distinguishing 3 types of research (sample surveys, experiments, and correlational studies); teaching random-sampling theory in the context of sample surveys, augmenting the conventional treatment with bootstrapping; and noting that random assignment fosters internal but not external validity. The additional principles are explaining the general logic for testing a null model; teaching randomization tests as well as t , F , and x-sup-2 ; and acknowledging the problems of applying inferential statistics in the absence of deliberately introduced randomness. (PsycLIT Database Copyright 1996 American Psychological Assn, all rights reserved)
  • Author(s):
    Posten, H. O.
    Editors:
    Grey, D. R., Holmes, P., Barnett, V., &amp; Constable, G. M.
    Year:
    1983
    Abstract:
    Access to a collection of computer programs for the classical distribution functions, particularly if these can be readily used interactively by any student, is an important teaching tool for teachers of probability and statistics. The availability of such a collection allows the teacher and student to concentrate on the concepts and development of probability and statistics with little if any emphasis on the details of determining probabilities from tables. Algorithms are presented that provide a useful array of methods for evaluating the classical distribution functions.
  • Author(s):
    Lock, R. H.
    Editors:
    Davidson, R., &amp; Swift, J.
    Year:
    1986
    Abstract:
    The demand for data in applied statistics courses has increased dramatically in recent years as the growth in computer technology has enabled students to perform more sophisticated analyses on larger and more complicated data sets. This has increased the burden on instructors and textbook authors to supply interesting data to illustrate desired concepts and allow students to practice techniques. We will describe some ways the computer itself can be used to help satisfy the demand for data.
  • Author(s):
    Robinson, D., &amp; Bowman, A.
    Year:
    1990
    Abstract:
    Discusses the use of computer-illustrated texts to teach statistics at the college level. Microcomputer-based software that can be used in the areas of calculation, graphics, simulation, animation, and text presentation is described; and use of the software for lectures, laboratory use, and tutorials is discussed. (three references) (LRW)
  • Author(s):
    Hudson, W. W.
    Year:
    1985
    Abstract:
    This paper describes a computer managed instruction package for teaching introductory or advanced statistics. The instructional package is described and anecdotal information concerning its performance and student responses to its use over two semesters are given. (Author/BL)
  • Author(s):
    Marasinghe, M.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    Marasinghe, Meeker, Cook, and Shin (1996) used graphical and simulation techniques to construct a system of computer-based modules for teaching statistical concepts. The software component of these modules consisted of a computer program written in LISP-STAT incorporating a highly interactive user interface. The instructional component is set of a prototype lessons providing information to instructors such as a description of concepts that may be illustrated with the program and possible exercises. Since then, the addition of several new modules have enhanced the usefulness of the system. In this paper we illustrate several of these modules useful for teaching concepts as different from how sample size and confidence level affects the width and coverage of confidence intervals to how variability affects precision of experimental results.

Pages

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