Literature Index

Displaying 3231 - 3240 of 3326
  • Author(s):
    Russell, S. J.
    Editors:
    Burrill, G. F.
    Year:
    2006
    Abstract:
    The article focuses on how elementary school students engage with developing a statistical question (how students learn about developing and refining a question for data collection) and the analysis part of the data. For the analytic part, how students make sense of their data once they are collected, e.g. how they relate graphs, numbers, and statistics back to their original question, is addressed in this article.
  • Author(s):
    Carver, R.
    Year:
    1998
    Abstract:
    In a residential home, energy consumption is closely related to the outdoor temperature and size of the house. In a home of a given size, fuel consumption varies fairly predictably through the year. When homeowners add a room, other things being equal, energy consumption should increase. This dataset permits students to estimate the energy demand, make forecasts for future months, and investigate other relationships.
  • Author(s):
    Andrew Zieffler, Joan Garfield, Shirley Alt, Danielle Dupuis, Kristine Holleque, and Beng Chang
    Year:
    2008
    Abstract:
    Since the first studies on the teaching and learning of statistics appeared in the research literature, the scholarship in this area has grown dramatically. Given the diversity of disciplines, methodology, and orientation of the studies that may be classified as "statistics education research," summarizing and critiquing this body of work for teachers of statistics is a challenging and important endeavor. In this paper, a representative subset of studies related to the teaching and learning of statistics in introductory, non-calculus based college courses is reviewed. As a result of this review, and in an effort to improve the teaching and learning of statistics at the introductory college level, some guidelines to help advance future research in statistics education are offered.
  • Author(s):
    Wilson, R. J.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    Teaching statistics to students aspiring to other professions can be both frustrating and rewarding. The frustration arises from (a) having limited time to cover everything from introductory to advanced material, (b) receiving little input from staff in the client profession, (c) the concepts of unpredictability and randomness being alien to students' thinking, particularly for engineering students, and (d) students not having the background knowledge or skills necessary to understand the methods fully. The reward comes from seeing students understand both basic and advanced concepts and methods, and from requests for assistance with later work as former students discover the relevance of statistics. This paper will address some methods used to overcome the frustration and to enhance the rewards in teaching a first course in statistics to engineering students. Although situations vary, these ideas will hopefully provide helpful tools.
  • Author(s):
    Utts, J.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    Much has changed since the widespread introduction of statistics courses into the curriculum in the 1960s and 1970s, but the way introductory statistics courses are taught has not kept up with those changes. This paper discusses the changes, and the way the introductory syllabus should change to reflect them. In particular, seven ideas are discussed that every student who takes elementary statistics should learn and understand in order to be an educated citizen. Misunderstanding these topics leads to cynicism among the public at best, and misuse of study results by physicians and others at worst.
  • Author(s):
    Scheaffer, R. L., Watkins, A. E., & Landwehr, J. M.
    Editors:
    Lajoie, S. P.
    Year:
    1998
    Abstract:
    Statistics is not about numbers, statistics is about numbers in context. Statistics is not the same as probability. But some probability is necessary to understand certain statistical topics, while other statistical topics do not depend on probability. Statistics is not the same as mathematics. But an appropriate level of mathematics is needed to understand any statistical topic, and understanding statistics can contribute to an understanding of mathematics. Statistics is not the same as the scientific method. Yet statistics helps solve problems in science, engineering, medicine, business, and many other fields. Using statistics is inherently interdisciplinary. While using statistics demands that one understand the problem, the reason that statistics is so powerful is that key statistical concepts, methods and ideas are applicable in so many different problem contexts. This paper discusses the key concepts in statistics that students must learn in the K-12 curriculum so that all high school graduates can become productive citizens and use quantitative information effectively. The topics are organized and discussed in terms of number sense, planning studies, data analysis, probability, and statistical or inferential reasoning.
  • Author(s):
    Landwehr, J. M. Schaeffer, R. L. Watkins, A. E.
    Year:
    1998
    Abstract:
    We depend on data to make intelligent decisions, yet the data we see is often "tainted." An old saying on the use and misuse of computers was "garbage in - garbage out" but this has become "garbagge in - gospel out" as more and more people get in to the numbers game. So, what can we do? Part of the answer lies in education. Comsumer and producers of data with sreious unbiased objectives to get at the "truth" must be educated in how surbeys an experiments work, how good surveys and experiments can be designed, and how data can be properly analyzed. Every high school graduate must be educated to be an intelligent consumer of data and to know enough about hte production of data to at least judge the value of data produced by others. This education must be built into the K-12 curriculum, primarily in mathematics and science but with consistent support and application from the social sciences, health and other academic subjects.
    Location:
  • Author(s):
    Horvath, J.K., & Lehrer,R.
    Year:
    1994
    Abstract:
    Performance based assessments of statistical thinking provide teachers with a window to students' conceptual development. With this aim in mind, we examined the performance of a pair of fourth/fifth-grade students working collaboratively on a probabilistic assessment task developed by the California Department of Education. To account for student performance, we developed a cognitive model of the knowledge guiding student performance. Using this cognitive model, we revised the assessment to provide opportunities for assisted performance. We believe that performance assessments of statistical thinking should be designed with ways to assist performance, a view consistent with visions of teaching and learning as assisted performance.
  • Author(s):
    Dietz, E. J.
    Year:
    1992
    Abstract:
    For faculty, summer camp provided an unusual teaching experience - a small group of motivated students in a highly interactive setting. For students, camp provided a glimpse of college life and an introduction to the field of statistics.
    Location:
  • Author(s):
    Weldon, K. L., & Tham, P.
    Editors:
    Vere-Jones, D., Carlyle, S., & Dawkins, B. P.
    Year:
    1991
    Abstract:
    This consideration of the question "What is basic statistics?" was initiated by an examination of training needs for statistics faculty at certain target universities in eastern Indonesia.

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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