Literature Index

Displaying 1131 - 1140 of 3326

  • Galton, Pearson, and the Peas: A Brief History of Linear Regression for Statistics Instructors

    Author(s):
    Stanton, J. M.
    Year:
    2001
    Abstract:
    An examination of publications of Sir Francis Galton and Karl Pearson revealed that Galton's work on inherited characteristics of sweet peas led to the initial conceptualization of linear regression. Subsequent efforts by Galton and Pearson brought about the more general techniques of multiple regression and the product-moment correlation coefficient. Modern textbooks typically present and explain correlation prior to introducing prediction problems and the application of linear regression. This paper presents a brief history of how Galton originally derived and applied linear regression to problems of heredity. This history illustrates additional approaches instructors can use to introduce simple linear regression to students.
    Location:
    http://www.amstat.org/publications/jse/v9n3/stanton.html

  • Gather, Organize, Display: Mathematics for the Information Society

    Author(s):
    Dickinson, J. C.
    Year:
    1986
    Abstract:
    Four activities are outlined that give students the opportunity to organize and display data. Selecting topics and various ways of displaying data with a microcomputer are discussed. (MNS)

  • Gedankensimulation: An intuitive way to communicate statistical ideas

    Author(s):
    Jones, K. S.
    Year:
    1992
    Abstract:
    Einstein called special physics experiments that he did in his head gedankenexperiments (which means "thought experiments"). Can such mental experiments, or simulations, be used in statistics? In this article, I'll provide some examples of how gedankensimulation can be be used either to illustrate an important idea or to help solve problems in probability and statistics.

  • Gender differences in performance on an a level mathematics paper

    Author(s):
    Rouncefield, M.
    Editors:
    Vere-Jones, D., Carlyle, S., & Dawkins, B. P.
    Year:
    1991
    Abstract:
    This research aims to replicate the study by Forbes (1988) who investigated gender differences in attainment in a Scholarship examination in mathematics. There are three major differences between this study and hers. First, this research is based on a mainstream Advanced Level examination paper rather than a Scholarship paper. Second, the study aims to discover whether the results found in New Zealand apply to pupils in Britain. Third, the examination paper includes questions on mechanics, which did not appear in the New Zealand examination, as well as statistics and pure mathematics. Following Forbes, the initial hypotheses are that girls and boys will perform equally well on some, at least, of the pure mathematics questions. There is also the opportunity to look for gender differences in attainment in mechanics questions.

  • Gender-related differences in self-referenced cognitions in relation to mathematics

    Author(s):
    Seegers, G., & Boekaerts, M.
    Year:
    1996
    Abstract:
    In this study, a number of learner variables that are related to mathematics achievement in actual learning situations were examined. The dynamic model of the learning process as developed by Boekaerts was taken as a starting point. Both trait-like self-referenced cognitions (viz., academic self-concept of mathematics ability, goal orientations, and attribution style) and situation-specific variables were included. In a group of 8th graders (ages 11-12; N=186), marked differences between boys and girls on a mathematics test were found. These differences were parallelled by differences in both trait-like self-referenced cognitions and task-specific appraisals. It is concluded that boys experience learning situations where they are confronted with a mathematics test in a more positive way than girls do.

  • Generating different data sets for linear regression models with the same estimates.

    Author(s):
    Zocchi, S. S., & Manly, B. F. J.
    Editors:
    Rossman, A., & Chance, B.
    Year:
    2006
    Abstract:
    For teaching purposes it is sometimes useful to be able to provide the students in a class with different sets of regression data which, nevertheless give exactly the same estimated regression functions. In this paper we describe a method showing how this can be done, with a simple example. We also note that the method can be generalized for situations where the regression errors are not independently distributed with a constant covariance matrix.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/17/C108.pdf

  • GERMAN MATHEMATICS TEACHERS' VIEWS ON STATISTICS EDUCATION

    Author(s):
    Peter Sedlmeier and Christoph Wassner
    Year:
    2008
    Abstract:
    Although knowledge about how to improve statistics teaching is steadily increasing, still very little is known about what statistics teachers actually know, think, and do in their classrooms. The present study is a first attempt to shed more light on the issue. Experienced mathematics teachers were asked about their views of statistics in general and of current curricula, as well as about their impressions of their students' views and abilities regarding statistics. In addition, they were asked to indicate what good statistics instruction should look like. We found that in general, teachers as well as students are quite interested in statistics but that students apparently experience greater difficulties in statistics classes than in classes on other mathematical topics. We identify several potential impediments to effective statistics instruction that might be good starting points for attempts to improve statistics education in German schools.
    Location:
    http://www.ugr.es/~icmi/iase_study/Files/Contents.htm

  • Getting an early start: Using interactive graphics to teach statistical concepts in high school

    Author(s):
    Rubin, A., Bruce, B., Rosebery, A., & DuMouchel, W.
    Year:
    1988
    Abstract:
    In order to educate high school students in statistical reasoning, we have developed, under National Science Foundation support, a computer-enhanced curriculum called Reasoning Under Uncertainty and microcomputer software called ELASTIC. The curriculum emphasizes reasoning and learning-by-doing as methods for helping students understand the hows and whys of statistics. The software is built on design principles of interactivity, visualization, and multiple, linked representations; it provides a laboratory in which students can explore the underlying meaning of abstract statistical concepts and processes. This paper describes the innovative aspects of the software and curriculum and the results of a field test in two high school classrooms- one urban, one suburban.

  • Getting More Data into Theoretical Statistics Courses

    Author(s):
    Moore, T. L.
    Editors:
    Winkel, B. J.
    Year:
    1992
    Abstract:
    At many small colleges the only statistics course offered to a mathematics major is the standard sequence in probability and mathematical statistics. This paper offers concrete suggestions on infusing this course with more data and applications so that students coming out of the course better appreciate the nature of statistics as a discipline separate from mathematics.

  • Getting Real Statistics into all Curriculum Subject Areas: Can Technology Make this a Reality?

    Author(s):
    Nicholson, James; Ridgway, Jim; McCusker, Sean
    Year:
    2013
    Abstract:
    Technology has revolutionised society and it has revolutionised the way in which statistics, as a professional discipline, is done. The collection of data is growing exponentially both in relation to the quantity of data assembled on any particular measure and also in relation to the range of topics, and the measures, on which data is collected. Accessing data has become much simpler, and tools for exploring, manipulating and representing that data visually have multiplied, both in commercially available software and open-source freeware. However, the curriculum in schools in the UK is constrained by important factors which restrict the use of technology in assessment. The statistics curriculum is largely dull and does not address the core issues of most relevance in statistics today. Here, we explore ways in which technology can enhance the teaching of subjects in which statistics are used, and also the teaching of statistics within mathematics.
    Location:
    http://escholarship.org/uc/item/7cz2w089

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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