Literature Index

Displaying 2081 - 2090 of 3326
  • Author(s):
    Oyelese, J. O.
    Editors:
    Barnett, V.
    Year:
    1982
    Abstract:
    This report discusses the current statistical education programs of primary and secondary schools in Nigeria
  • Author(s):
    Cheung, P. H., Lam, K., Siu, M. K., & Wong, N.Y.
    Editors:
    Davidson, R., & Swift, J.
    Year:
    1986
    Abstract:
    In the late sixties Hong Kong took her first step in introducing statistics into the secondary school mathematics curriculum as recommended by many national and international working groups in the mid fifties and early sixties. As statistics forms only a small portion of the entire mathematics syllabus, it is seldom singled out for inspection by mathematics educators in Hong Kong. We wish to take a first step in addressing this problem.
  • Author(s):
    Barnett, V.
    Editors:
    Barnett, V.
    Year:
    1982
    Abstract:
    This short review lists some literature on the Japanese statistical education.
  • Author(s):
    Howson, G.
    Editors:
    Goodall, G.
    Year:
    2002
    Abstract:
    This article critically explores several issues related to requirements for probability teaching in various national curricula.
  • Author(s):
    Bentz, H., & Borovcnik, M.
    Editors:
    Bell, A., Low, B., & Kilpatrick, J.
    Year:
    1984
    Abstract:
    In the following article some examples used in empirical investigations are discussed to show how difficult empirical research really is. A problem catalogue should have an impact on critical analysis of major research work in this field which is still to be done.
  • Author(s):
    Ulmer, M. B., & Scott, M.
    Editors:
    Vere-Jones, D., Carlyle, S., & Dawkins, B. P.
    Year:
    1991
    Abstract:
    In the United States, the topic of deficiency in quantitative literacy among high school graduates has been in the limelight for the past several years. Traditionally, students in US schools have not been taught statistics and probability as a regular course. The situation is particularly disappointing for many regions of the southeastern states which, in some respect, are similar to some of the developing nations around the world. We believe a long-term solution lies in nothing less than modification of requirements for mathematics teacher certification that include minimally the statistics objectives delineated by the NCTM Standards.
  • Author(s):
    Bar-Hillel, M., & Falk, R.
    Year:
    1982
    Abstract:
    A family of notorious teasers in probability is discussed. All ask for the probability that the objects of a certain pair both have some property when information exists that at least one of them does. These problems should be solved using conditional probabilities, but cause difficulties in characterizing the conditioning event appropriately. In particular, they highlight the importance of determining the way information is being obtained. A probability space for modeling verbal problems should allow for the representation of the given outcome and the statistical experiment which yielded it. The paper gives some psychological reasons for the tricky nature of these problems, and some practical tips for handling them.
  • Author(s):
    Sutarso, T.
    Year:
    1992
    Abstract:
    The purpose of this study was to investigate some variables that relate to students' anxiety in learning statistics. The variables included sex, class level, students' achievement, school, mathematical background, previous statistics courses, and race. The instrument used was the 24-item Students' Attitudes Toward Statistics (STATS), which was administered to the statistics classes at the College of Education and at the College of Commerce and Business Administration at the University of Alabama (Tuscaloosa). The STATS required students to describe themselves based on a 0 to 9 scale, with 0 being "does not describe me" and 9 being "describes me." The sample included 79 male and 97 female students in undergraduate and graduate statistics classes. The data were analyzed in contingency tables using chi square statistics to compute significance of relationships. All data analyses were performed on an IBM miniframe computer. The association analysis showed that there was a significant relationship between students' anxiety in learning statistics and the variables of students' achievement, statistical preknowledge, school, and current class level. However, the results do not provide enough evidence to suggest that there was a relationship between students' anxiety in learning statistics and the other variables (such as college mathematics background, gender, and ethnicity). (RLC)
  • Author(s):
    Russell, S. J., & Corwin, R. B.
    Year:
    1990
    Abstract:
    A unit of study that introduces sorting and classification as a way of organizing data is presented. Suitable for students in grades 2 and 3, it provides a foundation for further work in statistics and data analysis. The investigations may extend from one to five class sessions and are grouped into three parts: "Introduction to Sorting"; "Sorting and Classifying Data"; and "Projects in Data Analysis." An overview of the investigation, session activities, dialogue boxes, and teacher notes are included in each investigation. The major goals developed in each part of this guide are: (1) examining differences and similarities of objects or data; (2) decision making; (3) using negative information to clarify the definition of a category; (4) making sketches of data; (5) thinking flexibly about the characteristics of data; (6) articulating logical reasoning; (7) constructing categories to describe data; (8) inventing representations of data; (9) building theories about data; (10) collecting and recording survey data; (11) comparing two data sets; and (12) experiencing the phases of a data analysis investigation. Appended are reproducible student materials, including two sets of cards for developing sorting skills. (KR)
  • Author(s):
    Candace Schau, Michele Millar, and Peter Petocz
    Year:
    2012

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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