Literature Index

Displaying 251 - 260 of 3326

  • Alternatives To Scatterplots

    Author(s):
    Konold, C.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    Emerging evidence suggests that people do not have difficulty judging covariation per se but rather have difficulty decoding standard displays such as scatterplots. Using the data analysis software Tinkerplots, I demonstrate various alternative representations that students appear to be able to use quite effectively to make judgments about covariation. More generally, I argue that data analysis instruction in K-12 should be structured according to how statistical reasoning develops in young students and should, for the time begin, not target specific graphical representations as objectives of instruction.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/1/7f5_kono.pdf

  • Amount and kind of statistics to be taught to 16+ year olds

    Author(s):
    Eicker, F.
    Editors:
    Grey, D. R., Holmes, P., Barnett, V., & Constable, G. M.
    Year:
    1983
    Abstract:
    I will describe some personal experiences and ideas about teaching statistics and will propose a few methodological details and sources of applications useful at schools. The nature of statistical reasoning and selection of statistical school topics are also addressed.

  • An Active Learning Approach to Teach Advanced Multi-predictor Modeling Concepts to Clinicians

    Author(s):
    Gregory P. Samsa, Laine Thomas, Linda S. Lee, and Edward M. Neal
    Year:
    2012
    Abstract:
    Clinicians have characteristics – high scientific maturity, low tolerance for symbol manipulation and programming, limited time outside of class– that limit the effectiveness of traditional methods for teaching multi-predictor modeling. We describe an active-learning-based approach that shows particular promise for accommodating these characteristics.
    Location:
    http://ww2.amstat.org/publications/jse/v20n1/samsa.pdf

  • An active learning in-class demonstration of good experimental design

    Author(s):
    Anderson-Cook, C. M., & Dorai-Raj, S.
    Year:
    2001
    Abstract:
    This article presents an active learning demonstration available on the Internet using Java applets to show a poorly designed experiment and then subsequently a well-designed experiment. The activity involves student participation and data collection.
    Location:
    http://www.amstat.org/publications/jse/v9n1/anderson-cook.html

  • An active tutorial on distance sampling

    Author(s):
    Richardson, A.
    Year:
    2007
    Abstract:
    The technique of distance sampling is widely used to monitor biological populations. This paper documents an in-class activity to introduce students to the concepts and the mechanics of distance sampling in a simple situation that is relevant to their own experiences. Preparation details are described. Variations and extensions to the activity are also suggested..
    Location:
    http://www.amstat.org/publications/jse/v15n1/richardson.html

  • An Activity-Based Statistics Course

    Author(s):
    Gnanadesikan, M., Scheaffer, R. L., Watkins, A. E., & Witmer, J. A.
    Year:
    1997
    Abstract:
    So that students can acquire a conceptual understanding of basic statistical concepts, the orientation of the introductory statistics course must change from a lecture-and-listen format to one that engages students in active learning. This is the premise underlying an effort of the authors to produce and use a collection of hands-on activities that illustrate the basic concepts of statistics covered in most introductory college courses. Such activities promote the teaching of statistics more as an experimental science and less as a traditional course in mathematics. An activity-based approach enhances learning by improving the students' attention, motivation, and understanding. This paper presents examples of the types of activities that work well in various classroom settings along with comments from colleagues and students on their effectiveness.
    Location:
    http://www.amstat.org/publications/jse/v5n2/gnanadesikan.html

  • An algorithm and some results

    Author(s):
    Taveres, A. V.
    Editors:
    Vere-Jones, D., Carlyle, S., & Dawkins, B. P.
    Year:
    1991
    Abstract:
    The items covered in the paper are as follows: 1)teaching as an action leading the student towards a better understanding and interpretation of reality; 2)statistics as an area of knowledge that supplies scientific models closer to reality than classical deterministic ones; 3)the appeal of simplified models versus the risk of lack of rigour and of credibility; 4)the role of algorithmic computations versus laboratory simulation results.

  • An Analysis Of Secondary School Examination Syllabus, Public Examination Test Items And Statistical Literacy Level Of The Students

    Author(s):
    Chacko, I.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    The primary purpose of the study was to determine the extent to which the public examination test items in statistics reflect the syllabus aims and assessment objectives. In addition to this, the nature of responses of a group of final year secondary school students, to selected non-routine and routine items in statistics was also studied. The aims of the syllabus and assessment objectives as well as the suggested methodologies place emphasis on problem solving skills, discovery learning and application of learned concepts in real life situation where as examination items do not reflect these objectives. Students' responses to non-routine tasks too confirm their inability to handle anything that is not routine. Currently, certification is based on one shot examination, where items are routine in nature, which implies that teaching is geared towards preparing the students for the public examination. Certification, instead of depending on just one external examination, should move towards incorporating continuous assessment component thereby providing the opportunity to use projects and open - ended tasks as part of teaching and learning.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/1/10_31_ch.pdf

  • An Analysis of Students' Statistical Understandings

    Author(s):
    McGatha, M., Cobb, P., McCain, K.
    Year:
    1998
    Abstract:
    It is important to develop instructional sequences that build on students' current understandings and support shifts in their current ways of thinking. As part of the pilot work for a project on mathematics teaching, classroom performance assessments were conducted to obtain baseline data on students' current statistical understandings. The assessments were conducted in three sessions of a seventh-grade class. The assessment task was designed to provide information about students' current understandings of the mean and graphical representations of data because these ideas were the focus of a statistics chapter students previously studied. Students worked in small groups on the three performance tasks, each of which is described in detail. The analysis shows that students typically viewed the mean as a procedure that was to be used to summarize a group of numbers regardless of the task situation. Data analysis for these students meant "doing something with the numbers," an idea grounded in their previous mathematics experiences. Students' conversations about graphical representations highlight the procedures for constructing graphs with no attention to what the graphs signify and how that relates to the task situation. To help students develop a sense of data analysis as more than just "doing something with numbers," it is necessary to create tasks that are relevant to middle school students. An appendix contains a list of 69 sources for additional information. (Contains 8 figures and 11 references.) (SLD)

  • An analysis of the teacher's learning: A case from statistics

    Author(s):
    McClain, K.
    Year:
    2000
    Abstract:
    My purpose in this paper is to document the learning of one teacher as she interacted with a group of seventh-grade students over the course of a twelve-week research project focused on statistical data analysis.

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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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