Literature Index

Displaying 2511 - 2520 of 3326

  • Teaching Probability with the Support of the R Statistical Software

    Author(s):
    Robson dos Santos Ferreira, Verônica Yumi Kataoka, and Monica Karrer
    Year:
    2014
    Abstract:
    The objective of this paper is to discuss aspects of high school students’ learning of probability in a context where they are supported by the statistical software R. We report on the application of a teaching experiment, constructed using the perspective of Gal’s probabilistic literacy and Papert’s constructionism. The results show improvement in students’ learning of basic concepts, such as: random experiment, estimation of probabilities, and calculation of probabilities using a tree diagram. The use of R allowed students to extend their reasoning beyond that developed from paper-and-pencil approaches, since it made it possible for them to work with a larger number of simulations, and go beyond the standard equiprobability assumption in coin tosses.
    Location:
    http://iase-web.org/documents/SERJ/SERJ13(2)_Ferreira.pdf

  • Teaching probability: Didaktik der Stochastik

    Author(s):
    Kuetting, H.
    Year:
    1994
    Abstract:
    An approach to teaching probability. First the history of probability concepts are outlined, then the concept of probability is introduced. Two other chapters deal with using combinatorics to solve probability problems and factors affecting probabilistic judgements in children and students. Finally curricula in probability and statistics for grades 5 to 12 are discussed. At the end there is an extended bibliography of English, French and German literature.

  • Teaching Prospect Theory with the Deal or No Deal Game Show

    Author(s):
    Ardith Baker, Teresa Bittner, Christos Makrigeorgis, Gloria Johnson, Joseph Haefner
    Year:
    2010
    Abstract:
    Recent evidence indicates that decision makers are more sensitive to potential losses than gains. Loss aversion psychology has led behavioural economists to look beyond expected utility by developing prospect theory. We demonstrate this theory using the Deal or No Deal game show.
    Location:
    http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9639.2009.00390.x/abstract

  • Teaching random assignment

    Author(s):
    Rothenberg, L. F., & Sawilowsky, S. S.
    Year:
    1997
    Abstract:
    Random assignment is one of the more difficult concepts in introductory statistics classes. Many textbook authors admonish students to check on the comparability of two randomly assigned groups by conducting statistical tests on pretest means to determine if randomization worked. A Monte Carlo study was conducted on a sample of n = 2 per group, where each participant's personality profile was represented by 7,500 randomly selected and assigned scores. These values were obtained from real data sets from applied education and psychology research. Then, independent samples t-tests were conducted at the 0.01 alpha level on these scores. Results demonstrated that x-bar(1) does not equal x-bar(2) for only 33 out of 7,500 variables, indicating that random assignment was successful in equating the two groups on 7,467 variables, even with a sample size of n = 2. The students' focus is redirected from the ability of random assignment to create comparable groups to testing the claims of randomization schemes.

  • Teaching Rank-Based Tests by Emphasizing Structural<br>Similarities to Corresponding Parametric Test

    Author(s):
    DeWayne R. Derryberry, Sue B. Schou, and W. J. Conover
    Year:
    2010
    Abstract:
    Students learn to examine the distributional assumptions implicit in the usual t-tests and<br><br>associated confidence intervals, but are rarely shown what to do when those assumptions<br><br>are grossly violated. Three data sets are presented. Each data set involves a different<br><br>distributional anomaly and each illustrates the use of a different nonparametric test. The<br><br>problems illustrated are well-known, but the formulations of the nonparametric tests<br><br>given here are different from the large sample formulas usually presented. We restructure<br><br>the common rank-based tests to emphasize structural similarities between large sample<br><br>rank-based tests and their parametric analogs. By presenting large sample nonparametric<br><br>tests as slight extensions of their parametric counterparts, it is hoped that nonparametric<br><br>methods receive a wider audience.
    Location:
    http://www.amstat.org/publications/jse/v18n1/derryberry.pdf

  • Teaching reasoning

    Author(s):
    Nisbett, R. E., Fong, G. T., Lehman, D. R., &amp; Cheng, P.W.
    Year:
    1987
    Abstract:
    Twentieth-century psychologists have been pessimistic about teaching reasoning, prevailing opinion suggesting that people may possess only domain-specific rules, rather than abstract rules; this would mean that training a rule in one domain would not produce generalization to other domains. Alternatively, it was thought that people might possess abstract rules (such as logical ones) but that these are induced developmentally through self-discovery methods and cannot be trained. Research suggests a much more optimistic view: even brief formal training in inferential rules may enhance their use for reasoning about everyday life events. Previous theorists may have been mistaken about trainability, in part because they misidentified the kind of rules that people use naturally.

  • Teaching researchers to create linear models to solve practical problems

    Author(s):
    Ward, J. H., Polk, S. B., &amp; Alley, W. E.
    Editors:
    Vere-Jones, D., Carlyle, S., &amp; Dawkins, B. P.
    Year:
    1991
    Abstract:
    When it became apparent that many practical problems could not be solved by the standard procedures, a developmental effort began which combined the conceptual power of a prediction model approach with the computational power of high speed computers. A series of short courses were developed to introduce researchers to the new capabilities brought about through the combination of effective application of regression models with computing techniques.

  • Teaching spatial statistical techniques and concepts.

    Author(s):
    Castle, R.
    Editors:
    Rossman, A., &amp; Chance, B.
    Year:
    2006
    Abstract:
    The last decade has seen a rapid increase in the use of Geographical Information Systems (GIS) and the analysis of spatial data is an important component of this development. Spatial statistics is a relatively young subject and, although there are useful textbooks on spatial statistics theory, there is virtually no literature on how to teach spatial statistical concepts and techniques. This paper suggests ways of teaching some of spatial statistical analysis without recourse to matrix algebra and vectors. By using the graphical features in Excel it is possible to illustrate and explain the concepts behind the statistical techniques in GIS. The interactive and dynamic features of Excel enable students to investigate the effects of changing the spatial location of the data and to develop an understanding of spatial dependence and its impact on Kriging and regression techniques.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/17/7E3_CAST.pdf

  • Teaching SSE and Some of Its Applications in Junior High School

    Author(s):
    Bernard, J. E.
    Year:
    1986
    Abstract:
    This paper describes the development of curriculum materials for teaching the Sum of Squared Errors (SSE) to one class of 25 eighth graders in Hawaii. Microcomputers were used in class. Prior to explicit introduction of the SSE students were given repeated contact with a data base of various statistics collected from members of their class. Then a computer program was introduced which randomly selected values using the data base; students tried different guessing strategies. Worksheets were used in connection with this and other content; they are included in the paper. Interactive game-like situations were also used. The bridge to standard deviation was then described. Misconceptions that students may bring to the discussion of probability are described, with ways the developed materials sought to clarify the concepts. Finally, the application of SSE to linear regression is discussed. (MNS)

  • Teaching Statistical Concepts

    Author(s):
    Hawkins, A., Jolliffe, F., &amp; Glickman, L.
    Editors:
    Perrott, E.
    Year:
    1992
    Abstract:
    With the increasing recognition that statistics should be a part of the core curriculum for the compulsory years of schooling for all children, there is now an urgent need for teachers to be trained in both statistical content and appropriate teaching methods. this is a world-wide problem which is exacerbated because of the many changes which are currently taking place in the way in which statistics is practiced. This book lays the foundation for teachers' responses to these changes, exploring how best to teach those applied skills which are now seen to be a more relevant part of the content of statistics courses. It includes consideration of: changes taking place in statistics itself, for example in the areas of Exploratory Data Analysis, statistical computing and graphics; conceptual difficulties which face teachers and students of statistics and probability; research into statistical education; management of statistical project work; developments in teaching methods and materials; use and evaluation of teaching resources, including computer hardware and software, audio-visual aids and textbooks; assessment of statistical skills and understanding. Although teachers of advanced statistics courses will find the book of great interest, its main focus is on how to provide for the needs of the majority of students, namely those students who (although studying the subject in its own right, or combined with mathematics or other disciplines) do not intend to become specialist statisticians. Based on the authors' wide experiences of teaching statistics and statistical computing and their extensive knowledge of the related literature and research, the book provides a synthesis of ideas on the practicalities of teaching statistics, with a critical overview of relevant research into statistical education.

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