Literature Index

Displaying 1061 - 1070 of 3326
  • Author(s):
    Jacqueline R. Wroughton, Herle M. McGowan, Leigh V. Weiss, and Tara M. Cope
    Year:
    2013
    Abstract:
    Context provides meaning for data analysis and the evaluation of evidence but may be distracting to students. This research explores the role of context in students’ reasoning about sampling: specifically, the relationship between the strength of students’ opinions about a topic, which provides the context for a study, and their ability to judge the quality of the sampling method and the scope of the conclusions in the study. Data were collected at four diverse institutions in both a testing environment and through individual interviews. Student responses were analyzed using a grounded theory approach. Testing environment results showed little evidence of the use of context whereas interview results shows more evidence of reliance on context-bases opinions rather than statistical principles.
  • Author(s):
    Garfield, J. B., & delMas, R. C.
    Year:
    1990
    Abstract:
    This paper reports selected results from a larger study designed to investigate the stability of students' conceptions of probability. The "Reasoning About Chance Events" survey was administered to students both before and after the "Coin Toss" unit in order to identify consistent patterns of response as well as to capture changes in responses that might be caused by the instructional unit. Subjects in this study were first and second year college students from three sections of an introductory statistics courses.
  • Author(s):
    Alexander, M. T.
    Year:
    1992
    Abstract:
    Many commissions on education have warned that over the next decade, the U. S. will face a critical shortage of skilled workers thereby reducing the ability to compete globally. Numeracy (quantitative literacy) and the ability to put into effect quality improvement principles are among the critical skills workers need in preparing for the future. Businesses and educational institutions have targeted middle school students as the primary pools for these skilled workers and toward this goal have developed joint ventures to give these students an awareness of numeracy and quality improvement. This author has engaged in such a joint venture designed to interest Baltimore city middle-school students in pursuing careers in the Statistical and Quality Sciences.
    Location:
  • Author(s):
    Jennifer Harlow, Bry Ashman & Raazesh Sainudiin
    Year:
    2009
    Abstract:
    This paper discusses the development of graphical user interfaces (GUIs) to illustrate<br>sampling from a trinomial distribution by the natural extension of Galton's Quincunx to three<br>dimensions
  • Author(s):
    Tversky, A., &amp; Kahneman, D.
    Year:
    1983
    Abstract:
    Perhaps the simplest and the most basic qualitative law of probability is the conjunction rule: The probability of a conjunction, P(A&amp;B), cannot exceed the probabilities of its constituents, P(A) and P(B), because the extension (or the possibility set) of the conjunction is included in the extension of its constituents. Judgments under uncertainty, however, are often mediated by intuitive heuristics that are not bound by the conjunction rule. A conjunction can be more representative than one of its constituents, and instances of a specific category can be easier to imagine or to retrieve than instances of a more inclusive category. The representativeness and availability heuristics therefore can make a conjunction appear more probable than one of its constituents. This phenomena is demonstrated in a variety of contexts including estimation of word frequency, personality judgment, medical prognosis, decision under risk, suspicion of criminal acts, and political forecasting. Systematic violations of the conjunction rule are observed in judgments of lay people and of experts in both between-subjects and within- subjects comparisons. Alternative interpretations of the conjunction fallacy are discussed and attempts to combat it are explored.
  • Author(s):
    Stephanie Lem, Patrick Onghana, Lieven Verschaffel, and Wim Van Dooren
    Year:
    2013
    Abstract:
    Data distributions can be represented using different external representations, such as histograms and boxplots. Although the role of external representations has been extensively studied in mathematics, this is less the case in statistics. This study helps to fill this gap by systematically varying the representation that accompanies a task between participants, and assessing how university students use such representations in comparing aspects of data distributions. Following a cognitive fit approach, we searched for matches between items and representations. Depending on the item, some representations led to better achievement than other representations. However, due to the low overall accuracy rates and various difficulties that students displayed in interpreting these representations, we cannot make strong claims regarding matches between items and representations.
  • Author(s):
    Derek Christie
    Year:
    2008
    Abstract:
    This article shows how to use Microsoft Excel to get data from the Internet into a statistically usable form.
  • Author(s):
    Papanastasiou, E. C.
    Year:
    2005
    Abstract:
    Students at the undergraduate level usually tend to view research methods courses negatively. However, an understanding of these attitudes is necessary to help instructors facilitate the learning of research for their students, by enabling them to create more positive attitudes toward such courses. The aim of this study is to describe the development of an "attitudes toward research" scale and verify the dimensions of attitudes toward research among undergraduate students enrolled in introductory research courses. The basic hypothesis of this research study is that the concept of attitudes is multidimensional in nature. The sample of the study consisted of 226 students who had completed a research methods course. Based on a factor analysis, five factors of student attitudes toward research were identified. These were the factors of usefulness of research, anxiety, affect indicating positive feelings about research, life relevancy of research to the students' daily lives, and difficulty of research.
  • Author(s):
    Harraway, J. A.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    About 800 students each year enroll in a subject Introduction to Biostatistics at the University of Otago. It is a compulsory subject for students applying to enter the health sciences professional courses. At school there are two subjects, mathematics with calculus and mathematics with statistics, with many students studying only one of these the year before university. There is debate about which one best prepares students for gaining the high marks in biostatistics necessary for entry to the competitive professional health sciences programmes. The school syllabus in mathematics with statistics is first compared with that in Introduction to Biostatistics. Results from the analysis of marks achieved in biostatistics are reported. The fitted regression models show prior knowledge of statistics from the school subject has no effect on performance in biostatistics, that there is no gender effect and that prior knowledge of calculus may be beneficial. Reasons for these results are discussed and proposals made to improve the presentation of statistics to students of the health and biological sciences.
  • Author(s):
    Efraim Fischbein, Maria Sainati Nello &amp; Maria Sciolis Marino
    Year:
    1991
    Abstract:
    To investigate the origins and nature of intuitive obstacles affecting the learning of elementary probability theory, 618 Italian elementary and middle school students were interviewed about their methods of solution for several problems dealing with probability. The discussion focuses on four varieties of obstacles to learning prevalent within the findings of this study.

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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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