Literature Index

Displaying 671 - 680 of 3326

  • Conceptual Challenges facing A-Level Statistics Students: Teacher and Examiner Perspectives

    Author(s):
    Nicolson, J. & Mulhern, G.
    Editors:
    Starkings, S.
    Year:
    2000
    Abstract:
    This study sought to investigate perceptions of students' conceptual challenges among A-Level statistics teachers and examiners. The nature and extent of participants' insights were assessed using a questionnaire administered in either written form or via a semi-structured interview. The questionnaire comprised two sections: (i) free-response questions in which participants were asked to list the three most significant conceptual challenges faced by students; and (ii) an attitude scale designed to assess agreement with specific statements regarding possible conceptual challenges. Each section addressed five topic areas: regression and correlation, estimation, sampling methods, distribution modelling, and general statistical thinking. Forty-nine participants completed the questionnaire, though not all teachers were familiar with all of the topic areas. Results revealed interesting patterns of agreement and disagreement among participants with regard to students' conceptual difficulties and concomitant factors.
    Location:
    see Papers on Statistical Education from ICME-9 item #2834

  • Conceptual Challenges in Coordinating Theoretical and Data-centered Estimates of Probability

    Author(s):
    Cliff Konold; Sandra Madden; Alexander Pollatsek; Maxine Pfannkuch; Chris Wild; Ilze Ziedins; William Finzer; Nicholas J. Horton; Sibel Kazak
    Year:
    2011
    Abstract:
    A core component of informal statistical inference is the recognition that judgments based on sample data are inherently uncertain. This implies that instruction aimed at developing informal inference needs to foster basic probabilistic reasoning. In this article, we analyze and critique the now-common practice of introducing students to both "theoretical" and "experimental" probability, typically with the hope that students will come to see the latter as converging on the former as the number of observations grows. On the surface of it, this approach would seem to fit well with objectives in teaching informal inference. However, our in-depth analysis of one eighth-grader's reasoning about experimental and theoretical probabilities points to various pitfalls in this approach. We offer tentative recommendations about how some of these issues might be addressed
    Location:
    http://www.informaworld.com/smpp/title~db=all~content=g932654185

  • Conceptual Issues in Quantifying Unusualness and Conceiving Stochastic Experiments: Insights from Students’ Experiences in Designing Sampling Simulations

    Author(s):
    Luis Saldanha
    Year:
    2016
    Abstract:
    This article reports on a classroom teaching experiment that engaged a group of high school students in designing sampling simulations within a computer microworld. The simulation-design activities aimed to foster students’ abilities to conceive of contextual situations as stochastic experiments, and to engage them with the logic of hypothesis testing. This scheme of ideas involves imagining a population and a sample drawn from it, and an image of repeated sampling as a basis for quantifying a sampling outcome’s unusualness in terms of long-run relative frequency under an assumption about the population’s composition. The study highlights challenges that students experienced, and sheds light on aspects of conceiving stochastic experiments and conceiving a sampling outcome’s unusualness as a probabilistic quantity.
    Location:
    http://iase-web.org/documents/SERJ/SERJ15(2)_Saldanha.pdf

  • Conceptual understanding of the arithmetic mean

    Author(s):
    Leon, M. R., & Zawojewski, J. S.
    Year:
    1990
    Abstract:
    The present study had four purposes: a) to investigate children and adults' understanding of four component properties of the arithmetic mean, b) to determine the relative difficulty of these four component properties of the mean, c) to determine the differential potential of varied problem formats to facilitate understanding of the arithmetic mean, and d) to discuss differences between different types of methods for contributing to research about, and investigating understanding of the arithmetic mean.

  • Conceptualizing An Average As A Stable Feature Of A Noisy Process

    Author(s):
    Konold, C. & Pollatsek, A.
    Editors:
    Ben-Zvi, D. & Garfield, J.
    Year:
    2004
    Abstract:
    The idea of data as a mixture of signal and noise is perhaps the most fundamental concept in statistics. Research suggests, however, that current instruction is not helping students to develop this idea, and that though many students know, for example, how to compute means or medians, they do not know how to apply or interpret them. Part of the problem may be that the interpretations we often use to introduce data summaries, including viewing averages as typical scores or fair shares, provide a poor conceptual basis for using them to represent the entire group for purposes such as comparing one group to another. To explore the challenges of learning to think about data as signal and noise, we examine the "signal/noise" metaphor in the context of three different statistical processes: repeated measures, measuring individuals, and dichotomous events. On the basis of this analysis, we make several recommendations about research and instruction.

  • Conceptualizing Applied Statistics: A current need

    Author(s):
    Weinberg, S. L.
    Year:
    1993
    Abstract:
    In this paper, particular suggestions, borrowed from principles of effective teaching practice, are made to enable students to have a clear sense of the goals, sequence, and rationale for the course, and more generally, to engage students in meaningful and memorable learning. Finally, linkages should be clipped from newspaper and the popular press to illustrate the applicability to everyday life of the statistics being taught in class, and to make students understand how inundated they are with statistics on a daily basis, even though they probably do not realize it. A motivated student is an interested learner, and the more we, as instructors, can do to motivate our students, the more satisfied we can expect them to be.

  • Conditional probabilities: Insights and difficulties

    Author(s):
    Falk, R.
    Editors:
    Davidson, R., & Swift, J.
    Year:
    1986
    Abstract:
    Conditional probabilities play a central role in the process of inferring about the uncertain world. The formal definition of P ( A / B ) is easy and poses no problems. However, upon careful probing into students' ideas of conditional probabilities, some misconceptions and fallacies are uncovered. In this paper I wish to discuss three issues involving conditional probabilities that I believe require serious consideration and clarification by students and by teachers of probability. These issues are: Interpreting conditionality as causality, problems with defining the conditioning event, and confusion of the inverse.

  • Conditional probability and education reform: Are they compatible?

    Author(s):
    Rossman, A. J., & Short, T. H.
    Year:
    1995
    Abstract:
    We demonstrate that one can teach conditional probability in a manner consistent with many features of the statistics education reform movement. Presenting a variety of applications of conditional probability to realistic problems, we propose that interactive activities and the use of technology make conditional probability understandable, interactive, and interesting for students at a wide range of levels of mathematical ability. Along with specific examples, we provide guidelines for implementation of the activities in the classroom and instructional cues for promoting curiosity and discussion among students.
    Location:
    http://www.amstat.org/publications/jse/v3n2/rossman.html

  • Conditional probability: Its place in the mathematics curriculum

    Author(s):
    Watson, J. M.
    Year:
    1995
    Abstract:
    The late introduction of conditional probability in the curriculum statements is probably related to the automatic association of conditional probability with Bayes's theorem and the complicated analyses involving Venn diagrams or tree diagrams to work out the inverse probabilities in conditional problems. No doubt Bayes's theorem is a complex topic that is likely to be mastered by most students only at the senior secondary level. However, several other more straightforward uses can be made of conditional probability earlier in the curriculum. The examples that follow illustrate how conditional statement can be used to introduce conditional probabilities, how early applications can be found in sporting data, how independence can be introduced naturally, and how conditional probability can be related to data collection and presentation in two-way tables. These four topics can be introduced in grades 8 through 10.

  • Conduct and Presentation of a Statistical Survey: An Effective Way of increasing the Popularity of a 'Dry' Subject

    Author(s):
    Habibullah, S. N.
    Editors:
    Starkings, S.
    Year:
    2000
    Abstract:
    Speaking of the teaching and learning of statistics at the undergraduate level, a moderate amount of training in small-scale data-handling seems to be an indispensable part of an introductory program in statistics. (See {1}.) In the Pakistani system of statistical education, however, there is very little emphasis on the conduct of practical projects involving collection and analysis of real data. ( See {2}.) Realizing the importance of such projects, the Department of Statistics at Kinnaird College for Women, Lahore initiated a series of small-scale statistical surveys back in 1985. ( See {3}, {4} and {5}) Each of these surveys has consisted of (a) identification of a topic of interest, (b) formulation of a questionnaire, (c) collection of data from a sample of individuals / a population of interest, (d) a fairly detailed analysis of the collected data, and (e) presentation of the survey findings in front of teachers and students in the form of an educational and entertaining program. Combining information with other items of interest, such a program provides an effective forum for increasing the popularity of a discipline that is generally considered to be a tough and "dry" subject.<br><br>The following section of this paper throws light on various segments of the most recent one of these programs. The one which was held in the college hall on November 12, 1999, and in which a group of students belonging to the FA Second Year Statistics Class (grade 12, ages 17-18) presented salient features of a survey that had been carried out in order to explore the plus points as well as the problems experienced by the female nurses of Lahore (the author acting as compere/moderator for the program).
    Location:
    see Papers on Statistical Education from ICME-9 item #2834

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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