Literature Index

Displaying 2391 - 2400 of 3326
  • Author(s):
    Lutzer, D. J., Maxwell, J. W., & Rodi, S. B.
    Year:
    2000
    Abstract:
    Every CBMS survey continues longitudinal studies of fall term undergraduate enrollments in the mathematics programs of two-year colleges and in the<br>mathematics and statistics departments of four-year colleges and universities. Every CBMS survey includes departments that offer associate, bachelors, masters,<br>and doctoral degrees. Every CBMS survey also studies the demographics of the faculty in those programs and departments and examines the undergraduate curriculum to determine what is taught, who teaches it, and how it is taught. In addition, each CBMS<br>survey selects a family of special topics for study.<br><br>Chapter 1 of this report, and particularly the data highlights section of Chapter 1, gives an executive summary of CBMS2000 findings on the various longitudinal issues studied since 1965, presented at a broad level of aggregation. Individual tables are<br>discussed in more detail after the data highlights section. Chapter 2 presents CBMS2000 findings on the special topics chosen for the fall 2000 study. Subsequent chapters disaggregate Chapter 1 material. For example, Chapter 3 examines enrollment and curricular variations among four-year mathematics and statistics departments that offer bachelors, masters, or doctoral degrees as their highest degrees,<br>and Chapter 5 contains data on individual first-year courses. Chapter 4 presents four-year faculty demographic data broken down by department type. Chapters 6 and 7 present detailed studies of curricular and personnel issues in two-year college<br>mathematics programs.
  • Author(s):
    DICKINSON, Wendy B
    Year:
    2007
    Abstract:
    This paper describes three original assessments developed for use in undergraduate- and graduate-level mathematics and statistics courses: (a) the context-dependent item set (undergraduate); (b) the visual data display project (undergraduate); and (c) the statistics notebook (graduate). The goal of each assessment was to measure student learning of statistical concepts and methodology, gauge the student's ability to apply those concepts in context, and provide an opportunity for students to appreciate statistics as a way to investigate, summarize, and explain phenomena of interest. Examples of all three assessments and rubrics are available for presentation.
  • Author(s):
    Stein, S. H.
    Editors:
    Stephenson, W. R.
    Year:
    2005
    Abstract:
    Three basic theorems concerning expected values and variances of sums and products of random variables play an important role in mathematical statistics and its applications in education, business, the social sciences, and the natural sciences. A solid understanding of these theorems requires that students be familiar with the proofs of these theorems. But while students who major in mathematics and other technical fields should have no difficulties coping with these proofs, students who major in education, business, and the social sciences often find it difficult to follow these proofs. In many textbooks and courses in statistics which are geared to the latter group, mathematical proofs are sometimes omitted because students find the mathematics too confusing. In this paper, we present a simpler approach to these proofs. This paper will be useful for those who teach students whose level of mathematical maturity does not include a solid grasp of differential calculus.
  • Author(s):
    McClain, K. &amp; Cobb, P.
    Abstract:
    Describes the role of an instructional sequence and two accompanying computer-based tools in supporting students' developing understandings of statistical data analysis. Documents the emergence of the sociomathematical norm of what counts as a mathematical argument in the context of data analysis.
  • Author(s):
    Tzou, C., &amp; Cobb, P.
    Year:
    2000
    Abstract:
    My purpose in this paper is to analyze how students in one middle-school classroom came to understand the data creation process and the importance of that process to the drawing of conclusions from statistical data.
  • Author(s):
    McClain, K., Cobb, P., &amp; Gravemeijer, K.
    Editors:
    Burke, M.
    Year:
    2000
    Abstract:
    This paper describes how one group of students came to reason about data while developing statistical understandings related to exploratory data analysis. Episodes taken from a 7th grade classroom in which a 12-week teaching experiment was conducted are presented. One of the goals of the teaching experiment was to investigate ways to support middle school students' development of statistical reasoning proactively. The use of computer tools was viewed as an integral aspect of statistical reasoning rather than an add-on. Two computer tools were designed with the intention of supporting students' emerging mathematical notions while simultaneously providing them with tools for data analysis. The intent of the instructional sequences developed in the course of the teaching experiment is outlined first. The rest of the paper consists of descriptions of episodes from the classroom that highlight students' development of sophisticated ways to reason about data.
  • Author(s):
    McClain, K.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    This paper provides an analysis of a Teacher Development Experiment (Simon, 2000) designed to support teachers' understandings of statistical data analysis. The experiment addresses the following research question: Can the results from research conducted in a middle-grades mathematics classroom be used to guide teachers' learning? In both cases, activities from an instructional sequence designed to support the development of ways to reason statistically about data were the basis of engagement. Analyses of the episodes in this paper document that the learning trajectory that emerged from the teachers' activity did, in many significant ways, parallel that of the students.
  • Author(s):
    Agnoli, F., &amp; Krantz, D. H.
    Year:
    1989
    Abstract:
    This article discusses how intensional heuristics can be suppressed when alternative strategies are taught.
  • Author(s):
    Larry Ludlow and Kelsey Klein
    Year:
    2014
    Abstract:
    Correlated predictors in regression models are a fact of life in applied social science research. The extent to which they are correlated will influence the estimates and statistics associated with the other variables they are modeled along with. These effects, for example, may include enhanced regression coefficients for the other variables—a situation that may suggest the presence of a suppressor variable. This paper examines the history, definitions, and design implications and interpretations when variables are tested as suppressors versus when variables are found that act as suppressors. Longitudinal course evaluation data from a single study illustrate three different approaches to studying potential suppressors and the different results and interpretations they lead to.
  • Author(s):
    Hilton, S. C., Schau, C., &amp; Olsen, J. A.
    Year:
    2004
    Abstract:
    In addition to student learning, positive student attitudes have become an important<br>course outcome for many introductory statistics instructors. To adequately assess<br>changes in mean attitudes across introductory statistics courses, the attitude instruments used should be invariant by administration time. Attitudes toward statistics from 4,910 students enrolled in an introductory statistics course were measured using the Surveyof AttitudesToward Statistics(SATS)both at the beginning and at the end of the<br>semester. Confirmatory factor analysis on the covariance structure was used to determine the gender and time invariance properties of the SATS. Results indicate that the SATS is gender, time, and Gender &#729; Time invariant with respect to factor loadings and factor correlations. Gender was invariant with respect to 3 of the 4 factor variances;<br>variances from these same 3 factors were larger at the end than at the beginning of the<br>course.Having established that theSATSis factorially invariant with respect to gender,<br>time, and Gender &#729; Time, its component scores can be used appropriately to examine<br>mean attitude differences for these 2 variables and their interaction.

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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