Literature Index

Displaying 1331 - 1340 of 3326

  • Interpretation of psychological research survey

    Author(s):
    Forsyth, A., Arpey, S., & Stratton-Hess, C.
    Abstract:
    This is an actual survey that was used as part of a project designed to study how people interpret descriptions of psychological research studies.

  • Interpretation Of Regression Output: Diagnostics, Graphs, and the Bottom Line

    Author(s):
    Johnson, W. & Watnikk, M.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    A standard approach in presenting the results of a statistical analysis of regression data in scientific journals is to focus on the question of statistical significance of regression coefficients. The reporting of p-values in conjunction with a description of the various positive and negative associations between the response and the factors in question ensues. The real question of interest beyond these initial assessments ought to be, "how well does the treatment work?" The point of view taken here will be that this standard presentation, while important, constitutes only a first order approximation to a complete analysis, and that the bottom line ought to involve the quantification of regression effects on the scale of observable quantities. This will mainly be accomplished graphically. It is also emphasized that diagnostic assessment of the compatibility of the data to the model should be based on similar considerations.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/1/3b1_john.pdf

  • Interpretation of Statistical Data: The Importance of Affective Expressions

    Author(s):
    Tamires Queiroz, Carlos Monteiro, Liliane Carvalho, and Karen François
    Year:
    2017
    Abstract:
    In recent years, research on teaching and learning of statistics emphasized that the interpretation of data is a complex process that involves cognitive and technical aspects. However, it is a human activity that involves also contextual and affective aspects. This view is in line with research on affectivity and cognition. While the affective aspects are recognized as important for the interpretation of data, they were not sufficiently discussed in the literature. This paper examines topics from an empirical study that investigates the influence of affective expression during the interpretation of statistical data by final-year undergraduate students of statistics and pedagogy. These two university courses have different curricular components, which are related to specific goals in the future professional careers of the students. The results suggest that despite differing academic backgrounds in both groups, the participants’ affective expressions were the most frequent type of category used during the interpretation of research assignments.  
    Location:
    http://iase-web.org/documents/SERJ/SERJ16(1)_Queiroz.pdf

  • Interpreting probabilities and teaching the subjective viewpoint.

    Author(s):
    Albert, J.
    Editors:
    Burrill, G. F.
    Year:
    2006
    Abstract:
    On the basis of the literature on children's probabilistic conceptions and on the results of a survey of introductory statistics college students, this article argues that subjective probability should play a larger role in the probability curriculum in the schools. Also, a simple method for teaching conditional probability and illustrate Bayesian thinking is described. Other activities that are useful for applying subjective and alternative probability interpretations are suggested.

  • Interpreting students' interpretations of research

    Author(s):
    May, R. B., & Hunter, M. A.
    Year:
    1988
    Abstract:
    This article examines the role of random sampling and random assignment in the interpretation of research results. We discuss the random assignment model, which focuses on causal inference, and recommend that both models be taught in introductory methods and statistics courses.

  • Interrelated learning and working environment for supporting the use of computer tools in introductory statistics

    Author(s):
    Biehler, R.
    Year:
    2003
    Abstract:
    At the department of mathematics &amp; informatics in our University we are in the process of<br>redesigning our introductory course on stochastics (probability and statistics) for future<br>mathematics teachers. In this course we now use the software FATHOM, which students learn as a (cognitive and culturally mediated) tool for exploratory data analysis, for simulation and for inferential statistics as well as a tool for experimenting with statistical methods. We use various types of Internet based materials to support the learning process of our students. Experimental learning environments and working environments containing data and exploratory guides are constructed with FATHOM. FATHOM offers meta-medium and meta-tool capabilities that offer high adaptability and versatility for the teacher of a course. In addition, we have developed Java applets, screen videos and web-based hypertexts as further
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/6/Biehler.pdf

  • Intricacies of statistical inference and teachers' understandings of them.

    Author(s):
    Thompson, P., Liu, Y., &amp; Saldanha, L.
    Editors:
    Lovett, M. C., &amp; Shah, P.
    Year:
    2007

  • Intriguing Facets Of Institution Research

    Author(s):
    Vermeulen, P. J.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    The higher education landscape, all over the world, is in constant flux. A changing external and internal environment is not a new phenomenon in higher education but is an inherent characteristic of the higher education system over centuries. The Association for Institutional Research (AIR) was established in the United States of America in 1959. The relevant burning issues confronting higher education institutions in the USA at that point in time, and which gave rise to the need for the establishment of such an association shows that while similar issues as those in the early nineteen sixties still exist, the strategies and solutions to the problems differ substantially from those of the past, mainly due to the advancement of technology.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/1/4k4_verm.pdf

  • Introducing box and whisker plots

    Author(s):
    Carr, J., &amp; Begg, A.
    Year:
    1994
    Abstract:
    Box and whisker plots were introduced to a group of eight students for enrichment and foolow-up sessions as part of a project looking at the ideas that 11 and 12-year-olds have about central tendency and dispersion. This paper reports some tentative findings about the teaching and learning of box and whisker plots to middle-school children.

  • Introducing data analysis in a statistics course in environmental science studies.

    Author(s):
    Capilla, C.
    Editors:
    Rossman, A., &amp; Chance, B.
    Year:
    2006
    Abstract:
    Education in methods of applied statistics is important for students who will be involved in management and decision-making processes. This paper discusses issues related to the teaching of statistics to students enrolled in an undergraduate environmental science degree course. The aim is to describe the teaching of graphical and numerical methods for summarizing and exploring data obtained in environmental studies. The application of descriptive and exploratory methods provides useful information regarding the distribution of the data at hand and of its patterns and associations. These methods are presented at the beginning of the course, following an introduction to the steps involved in the process of learning from data through the use of statistics. Students are instructed in the reading and interpretation of graphic and numeric data summary techniques. The importance of visualizing the main patterns and associations in the data is emphasized using environmental examples.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/17/4E1_CAPI.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

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