Literature Index

Displaying 3011 - 3020 of 3326
  • Author(s):
    Lajoie, S. P.
    Year:
    2003
    Abstract:
    The transition from student to expert professional can be accelerated when a trajectory for change is plotted and made visible to learners. Trajectories or paths toward expertise are domain specific and must first be documented and then used within instructional contexts to promote knowledge transitions. This article describes how models of expertise can serve to help students attain higher levels of competence.
  • Author(s):
    Morrell, C. H., Auer, R. E.
    Year:
    2007
    Abstract:
    In the early 1990's, the National Science Foundation funded many research projects for improving statistical education. Many of these stressed the need for classroom activities that illustrate important issues of designing experiments, generating quality data, fitting models, and performing statistical tests. Our paper describes such an activity on logistic regression that is useful in second applied statistics courses. The activity involves students attempting to toss a ball into a trash can from various distances. The outcome is whether or not students are successful in tossing the ball into the trash can. This activity and the adjoining homework assignments illustrate the binary nature of a response variable, fitting and interpreting simple and multiple logistic regression models, and the use of odds and odds ratio
  • Author(s):
    Krevisky, S.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    In basic Statistics classes, we are often interested in "Tree Diagrams", which provide a visual way for our students to compute how many ways various events can occur. One special example of this is the US National Collegiate Association of America (NCAA) Basketball tournament, which takes place in March of each year. Fans get caught up in "March Madness," and enjoy trying to predict the "Final Four". In this paper, we discuss many aspects of this tournament, including sharing of what the Tree diagram looks like, various probabilities of what different teams will do, and making predictions about what will happen in the First Round and beyond.
  • Author(s):
    Edgell, J. J.
    Editors:
    Vere-Jones, D., Carlyle, S., & Dawkins, B. P.
    Year:
    1991
    Abstract:
    What follows are some suggestions upon module developments designed to provide problem-solving experiences in developing a sequence of trigonal,numerical arrays, JE(n), which in turn give rise to sequences of discrete, fair probability spaces, P(m(JE(n))), with practical suggestions for open-ended model building. Hopefully these module developments will give some insight into teaching and learning some aspects of problem-solving, as well as naturally generating probability spaces which are discrete and fair. The intent is that the module will contribute to the student's overall ability to understand probability and statistics at a more mature level of sophistication. These ideas were initiated about 1983 by the author, have been field tested with two groups of fifth grade students successfully, and many teachers at the public school level and university level have benefited from workshops based upon these modules.
  • Author(s):
    MARY, C. & GATTUSO, L.
    Year:
    2005
    Abstract:
    The results are taken from a much larger study on the strategies that pupils in the 2nd, 3rd and 4th stages at secondary school (ages 14-16) use for solving problems concerning the mean. In this paper the solutions of three problems are analysed. These problems have been formulated to be of such a kind that we can distinguish between the ability of pupils to calculate a mean, and that of realising the effect of a change in the number of observations or in the value of an observation, on the mean. The problems were also seen to test the influence of a value equal to zero on the mean, drawn attention to in earlier research studies. The results of the current study show us, in the chosen context, the type and sense of the modifications exerting influence on the manipulations of the pupils, and that inadequate conceptions or a change of meaning appeared in certain situations and not in others. Note: An extended summary in English is provided at the beginning of this paper, which is written in French.
  • Author(s):
    Paul F. Velleman
    Year:
    2008
    Abstract:
    Statisticians and Statistics teachers often have to push back against the popular impression that Statistics teaches how to lie with data. Those who believe incorrectly that Statistics is solely a branch of Mathematics (and thus algorithmic), often see the use of judgment in Statistics as evidence that we do indeed manipulate our results.<br><br>In the push to teach formulas and definitions, we may fail to emphasize the important role played by judgment. We should teach our students that they are personally responsible for the judgments they make. But we must also offer guidance for their statistical judgments. Such guidance requires that we acknowledge the role of ethics in Statistics. The principle guiding these judgments should be the honest search for truth about the world, and the principle of seeking such truth should have a central place in Statistics courses.<br><br>The remark attributed to Disraeli would often apply<br>with justice and force: "There are three kinds of lies:<br>lies, damn lies, and statistics".<br>-Mark Twain<br><br>This may be my least favorite quotation about Statistics. But I wish to address what underlies both the quotation and the gleeful willingness of many who know nothing at all about Statistics to quote it as if it justified their low opinion of the discipline.<br><br>This quotation has infiltrated discussions in many disciplines. Surely you have had it quoted back to you if you were foolish enough to admit in polite company that you teach Statistics. Nigel Rees's Quote...Unquote1 claims that this is the single most quoted remark in the British media.2 A Google books search of "lies, damn lies, and statistics" turns up 495 books, and a general Google search finds "about 207,000" hits. A small (nonrandom) sample of these references shows that most are meant to suggest dishonest manipulations and interpretations.
  • Author(s):
    Boland, P. J., &amp; Pawitan, Y.
    Year:
    1999
    Abstract:
    In the lottery game Lotto n/N, the winning n numbers are selected randomly and without replacement from {1, 2, 3, ..., N}. The selection of the winning numbers is normally done with a highly sophisticated mechanical device, and one of the appealing aspects of Lotto is that this procedure is seen to be fair and unbiased. An important perceived consequence is that no one (for a given amount of money) is seen to have a better chance of winning than anyone else. Few people would be willing to let an individual perform this task because of possible bias, but do we really know how difficult it is for an individual to be random in selecting numbers? In an experiment to observe the types and degrees of bias an individual might possess, data were collected from students who were asked to perform as 'random' number generators for the Lotto 6/42 game. Data consisting of the winning numbers from the Irish National Lottery game Lotto 6/42 were obtained from previous years, and a statistical package (in this case, S-Plus) was used to generate other simulated data. A comparison of the three sets of data using many of the basic tools in descriptive statistics together with some goodness of fit tests provides a useful exercise for students to test their intuition about randomness and to discover some of the inherent (and sometimes subtle) biases individuals possess when they attempt to be random.
  • Author(s):
    Dawson, R. J. M.
    Year:
    1997
    Abstract:
    Despite advances in computer technology, quantiles of Student's t (among other distributions) are still calculated using printed tables in most classroom situations. Unfortunately, the structure of the tables found in textbooks (and even in books of tables) is usually better suited to fixed-level hypothesis testing than to the p-value approach that many modern statisticians favor. This article presents a novel arrangement of the table that allows p-values to be determined quite precisely from a table of manageable size.
  • Author(s):
    Serlin, R. C., &amp; Levin, J. R.
    Year:
    1996
    Abstract:
    The common development of the hypergeometric probability formula is typically confusing to students in introductory statistics courses. Two alternative developments that appear to be more intuitive and conceptually consistent are presented.
  • Author(s):
    Kady Schneiter
    Year:
    2008
    Abstract:
    Interactive applets have the ability to enhance statistics teaching by providing multiple representations of new concepts and by facilitating experimentation. I introduce two applets that have been developed as aids in illustrating ideas relevant to hypothesis testing and describe how I have used these in my classes.

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