Literature Index

Displaying 931 - 940 of 3326
  • Author(s):
    Weaver, K. A.
    Year:
    1992
    Abstract:
    Most statistics teacher strive to make the course material meaningful. This article presents specific examples for elaborating the statistical concepts of variability, null hypothesis testing, and confidence interval with common experience.
  • Author(s):
    Rubin, A., Rosebery, A. S., & Bruce, B.
    Year:
    1988
    Abstract:
    Our analysis identified problems both with the subject matter of statistics (e.g. multiple levels of abstraction, difficulty mapping statistical representations to real-world situations) and with its pedagogy (which typically does little to help concertize abstract concepts or illuminate the mapping process). Drawing on research in education, cognitive psychology and statistical computing, we designed, implemented, and pilot-tested software (ELASTIC) and a curriculum (Reasoning Under Uncertainty) to address these problems. Our approach was successful in many of the problem areas identified above; in addition, our experiences in classrooms helped us better understand the difficulties students have in understanding and applying statistical reasoning.
  • Author(s):
    Rubin, A., Rosebery, A. S., & Bruce, B.
    Year:
    1988
    Abstract:
    Our analysis identified problems both with the subject matter of statistics (e.g. multiple levels of abstraction, difficulty mapping statistical representations to real-world situations) and with its pedagogy (which typically does little to help concertize abstract concepts or illuminate the mapping process). Drawing on research in education, cognitive psychology and statistical computing, we designed, implemented, and pilot-tested software (ELASTIC) and a curriculum (Reasoning Under Uncertainty) to address these problems. Our approach was successful in many of the problem areas identified above; in addition, our experiences in classrooms helped us better understand the difficulties students have in understanding and applying statistical reasoning.
  • Author(s):
    McLaren, C. H., & McLaren, B. J.
    Year:
    2003
    Abstract:
    The Electric Bill dataset contains monthly household electric billing charges for ten years. In addition, there are values for such potential explanatory variables as temperature, heating and cooling degree days, number in household, and indicator variables for a new electric meter and new heat pumps. The values provide a real dataset to use for applications ranging from simple graphical analysis through a variety of time series and causal forecasting methods. The dataset also is suited to spreadsheet applications for break-even calculations and optimization. With knowledge of the utility's tiered rate function, the bill amount can be converted to an estimate of the number of kilowatt hours used. A series of assignment questions is included and the accompanying Instructor's Manual provides solutions.
  • Author(s):
    Canada, D.
    Editors:
    Gal, I., & Short, T.
    Year:
    2006
    Abstract:
    While other research has begun to contribute to our understanding of how pre-college students reason about variation, little has been published regarding pre-service teachers' statistical conceptions. This paper summarizes a framework useful in examining elementary pre-service teachers' conceptions of variation, and investigates the question of how a class of pre-service teachers' responses concerning variation in a probability context compare from before to after class interventions. The interventions comprised hands-on activities, computer simulations, and discussions that provided multiple opportunities to attend to variation. Results showed that there was overall class improvement regarding what subjects expected and why, in that more responses after the interventions included appropriate balancing of proportional thinking along with an appreciation of variation in expressing what was likely or probable.
  • Author(s):
    Kazak, S., & Confrey, J.
    Editors:
    Rossman, A., & Chance, B.
    Year:
    2006
    Abstract:
    Data and chance are the two related topics that deal with uncertainty. On the discussions of probability and statistics in both research and instruction, the existing literature depicts an artificial separation, to which other researchers (Shaughnessy, 2003; Steinbring, 1991) have already called attention in recognition of the inseparable nature of data and chance. Hence, this paper addresses how to integrate the discussions of distributions and probability, starting from the elementary grades. We report on a study that examines fourth-grade students' informal and intuitive conceptions of probability and distribution through a sequence of tasks for developing their understandings about probability distributions. These tasks include various random situations that students explore with a set of physical chance mechanisms and that can be modeled by a binomial probability distribution.
  • Author(s):
    Sibel Kazak and Jere Confrey
    Editors:
    Carmen Batanero
    Year:
    2007
    Abstract:
    This research focuses on fourth-grade (9-year-old) students' informal and intuitive<br>conceptions of probability and distribution revealed as they worked through a sequence of tasks. These<br>tasks were designed to study students' spontaneous reasoning about distributions in different settings and<br>their understanding of probability of various binomial random events that they explored with a set of<br>physical chance mechanisms. The data were gathered from a pilot study with four students. We analyzed<br>the interplay of reasoning about distribution and understanding of probability. The findings suggest that<br>students' qualitative descriptions of distributions could be developed into the quantification of probabilities<br>through reasoning about data in chance situations.
  • Author(s):
    Timothy Jacobbe and Robert M. Horton
    Year:
    2010
    Abstract:
    This study investigated elementary school teachers' comprehension of data displays. Assessment, interview, and observation data were analyzed to determine their level of comprehension. Results revealed that the teachers were proficient at "reading the data" and computation types of "reading between the data" questions, but were unsuccessful with questions that assessed higher levels of graphical comprehension. Many of the difficulties exhibited by the teachers appear to be attributable to a lack of exposure to the content. Implications for teacher preparation, professional development, and curricula development are discussed.
  • Author(s):
    Tim Jacobbe
    Year:
    2008
    Abstract:
    This paper presents results from a case study that explored elementary school teachers' understanding of essential topics in statistics. Teachers' understanding of the mean and median is presented in light of the suggestions by the GAISE document at Level A. It is important to consider where inservice teachers' understanding currently lies as we explore issues related to improving the sophistication of teaching and learning statistics in elementary schools.
  • Author(s):
    Timothy Jaccobe &amp; Robert M. Horton
    Year:
    2010
    Abstract:
    This study investigated elementary school teachers' comprehension of data displays. Assessment, interview, and observation data were analyzed to determine their level of comprehension. Results revealed that the teachers were proficient at "reading the data" and computation types of "reading between the data" questions, but were unsuccessful with questions that assessed higher levels of graphical comprehension. Many of the difficulties exhibited by the teachers appear to be attributable to a lack of exposure to the content. Implications for teacher preparation, professional development, and curricula development are discussed.

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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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