Literature Index

Displaying 171 - 180 of 3326
  • Author(s):
    Pollatsek, A., & Konold, C.
    Year:
    1990
    Abstract:
    In their article Ayton, Hunt and Wright (1989) address a number of issues that impinge on the concept of randomness. They appear to question not only the methodological soundness and general implications of research on "misconceptions" in statistics, but also the soundness of aspects of statistical inference. We concentrate here on a few key issues about which we are in disagreement (we think) with the authors.
  • Author(s):
    James Nicholson and Jim Ridgway
    Year:
    2017
    Abstract:
    White and Gorard make important and relevant criticisms of some of the methods commonly used in social science research, but go further by criticising the logical basis for inferential statistical tests. This paper comments briefly on matters we broadly agree on with them and more fully on matters where we disagree. We agree that too little attention is paid to the assumptions underlying inferential statistical tests, to the design of studies, and that p-values are often misinterpreted. We show why we believe their argument concerning the logic of inferential statistical tests is flawed, and how White and Gorard misrepresent the protocols of inferential statistical tests, and make brief suggestions for rebalancing the statistics curriculum.
  • Author(s):
    Huntley, M. A., Zucker, A. A., & Estey, E. T.
    Year:
    2000
    Abstract:
    This paper is organized so that over arching themes from the research are presented, followed by brief summaries of findings about particular topics centeral to the use of spreadsheets/graphing tools and data analysis/probability tools. The research summaries themselves and information about specific software follow. These summaries were written with a focus on the effects of mathematics software on middle grades students' learning of mathematics as well as impacts on other types of outcomes. The primary focus of this paper is on research about students' use of spreadsheets, data analysis/statistics, and probability software. The secondary focus is on research about graphing software.
  • Author(s):
    Cryer, J. D.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    This paper reviews the principal lessons for statistics education for business that can be drawn from the 17 annual U.S. Conferences held so far called Making Statistics More Effective in Schools and Business. The series of Conferences was begun in 1986 under the leadership of Professors Harry Roberts and George Tiao, both of the Graduate School of Business, The University of Chicago. "The mission of the annual Making Statistics More Effective In Schools and Business (MSMESB) conference is to improve the teaching and practice of Statistics in Schools of Business. We aim to encourage interaction between business faculty and others involved in teaching business statistics to business students, as well as interaction with professionals from industry and government, with publishers, and with software producers."
  • Author(s):
    delMas, R. C.
    Year:
    2002
    Abstract:
    One of the most challenging aspects of teaching statistics is helping students to understand concepts of randomness and probability. Research reveals that sutdents bring many misconceptions to their study of probability that are difficult to eradicate. Moreover, experience indicates that students often find the study of probability to be very frustrating and often disconnected from the study of statistics.
  • Author(s):
    Jones, P., Lipson, K., & Phillips, B.
    Editors:
    Brunelli, L., & Cicchitelli, G.
    Year:
    1993
    Abstract:
    It is not the purpose of this paper to delve into the reasons why the particular software being used may or may not be effective, although this is in itself an extremely important issue. Our purpose is to suggest a rationale as to why computer based simulations are not as helpful as we might suppose, and to propose an alternative path leading to statistical inference, which potentially avoids this problem.
  • Author(s):
    Shaklee, H., & Tucker, D.
    Year:
    1980
    Abstract:
    Several strategies are proposed as bases for judgments of covariation between events. Covariation problems were structured in such a way that patterns of correct and incorrect judgments would index the judgment rule being used by a given subject. In two experiments, 10th-grade or college subjects viewed a set of covariation problems, each of which consisted of a set of observations in which each of two events was defined as present or absent. Subjects were asked to identify the relationship between the events. Subjects' response patterns suggested that the modal strategy was to compare frequency of confirming and disconfirming events in defining the relationship. Response accuracy was influenced by pretraining on the concept of covariation and by response format. Instructions to sort the observations did not influence judgment accuracy.
  • Author(s):
    Smith , M. H.
    Year:
    2004
    Abstract:
    Unless the sample encompasses a substantial portion of the population, the standard error of an estimator depends on the size of the sample, but not the size of the population. This is a crucial statistical insight that students find very counterintuitive. After trying several ways of convincing students of the validity of this principle, I have finally found a simple memorable activity that convinces students beyond a reasonable doubt. As a bonus, the data generated by this activity can be used to illustrate the central limit theorem, confidence intervals, and hypothesis testing.
  • Author(s):
    Sahai, H., Khurshid, A., & Misra, S. C.
    Year:
    1996
    Abstract:
    This article presents an extensive collection of references on the teaching of probability and statistics. The bibliography includes articles published in statistical and subject-matter journals and in conferences.
  • Author(s):
    Bishop, G.
    Year:
    1998
    Abstract:
    This paper outlines one of a series of tutorials developed as part of an introductory statistics course for Agricultural and Natural Resource Sciences students. Here we compare two methods of sampling from an aerial photograph to obtain an estimate of the proportion of a particular type of vegetation. One method, transect sampling, is traditionally used by field ecologists, while the other is simple random sampling in a plane. Preparation details and possible extensions to the tutorial are described.

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