# Literature Index

Displaying 3151 - 3160 of 3326
• ### Using R in Introductory Statistics Courses with<br>the pmg Graphical User Interface

Author(s):
John Verzani
Year:
2008
Abstract:
The pmg add-on package for the open source statistics software R is described. This package provides a<br>simple to use graphical user interface (GUI) that allows introductory statistics students, without<br>advanced computing skills, to quickly create the graphical and numeric summaries expected of them.
• ### Using R to Simulate Permutation Distributions for Some<br>Elementary Experimental Design

Author(s):
T. Lynn Eudey, Joshua D. Kerr, and Bruce E. Trumbo
Year:
2010
Abstract:
Null distributions of permutation tests for two-sample, paired, and block designs are simulated<br><br>using the R statistical programming language. For each design and type of data, permutation<br><br>tests are compared with standard normal-theory and nonparametric tests. These examples (often<br><br>using real data) provide for classroom discussion use of metrics that are appropriate for the data.<br><br>Simple programs in R are provided and explained briefly. Suggestions are provided for use of<br><br>permutation tests and R in teaching statistics courses for upper-division and first year graduate<br><br>students
• ### Using real applications in the teaching of probability theory

Author(s):
Bungartz, P.
Editors:
Vere-Jones, D., Carlyle, S., &amp; Dawkins, B. P.
Year:
1991
Abstract:
Students should gain an insight into the usefulness of what they have learned in class such as the applicability of formulae, ideas, and methods. They should also have the opportunity of developing hypotheses and proving theorems. Probability theory and statistics provide many suitable ways for learning about these concepts. Students will be motivated to learn mathematics by using it to solve real problems. Consider, for example, a discussion of the risks associated with nuclear reactors - we should all be able to critically evaluate official statements and the arguments of so-called experts which are based on apparently legitimate mathematical methods. Looking at real applications in mathematics lessons, students get an insight into the part mathematical sciences play in the real world. We shall give three examples to illustrate our ideas.
• ### Using real data and technology to develop statistical thinking.

Author(s):
Connor, D., Davies, N., &amp; Holmes, P.
Editors:
Burrill, G. F.
Year:
2006
Abstract:
This article describes some internet-based projects using real data produced and collected from students in the United Kingdom and elsewhere. We believe that these projects enable students to understand better the reasons for data collection and ad a dimension to their learning.
• ### Using Real Life Examples to Teach Abstract Statistical Concepts

Author(s):
Nyaradzo Mvududu, Gibbs Y. Kanyongo
Year:
2011
Abstract:
This article provides real life examples that can be used to explain statistical concepts. It does not attempt to be exhaustive, but rather, provide a few examples for selected concepts based on what students should know after taking a statistics course
• ### Using Real-Life Data When Teaching Statistics: Student Perceptions of this Strategy in an Introductory Statistics Course

Author(s):
David L. Neumann, Michelle Hood, and Michelle M. Neumann
Year:
2013
Abstract:
Many teachers of statistics recommend using real-life data during class lessons. However, there has been little systematic study of what effect this teaching method has on student engagement and learning. The resent study examined this question in a first-year university statistics course. Students (n=38) were interviewed and their reflections on the use of real-life data during the classes were coded into themes. Resulting themes were (a) relevant perspective in learning, (b) interest, (c) learn/remember material, (d) motivation, (e) involvement/engagement, and (f) understanding of statistics. The results indicate both cognitive and affective/motivational factors are associated with using real-life data to teach statistics. The results also suggest the features in data sets statistics teachers should look for when designing their lessons.
• ### Using regression to connect algebra to the real world.

Author(s):
Bohan, J.
Editors:
Burrill, G. F.
Year:
2006
Abstract:
This article describes the use of regression in middle school grades and Algebra 1 settings to connect algebraic functions to real-world contexts. It is suggested that using data sets will intrigue and motivate students.
• ### Using Resampling to Compare Two Proportions

Author(s):
W. Robert Stephenson, Amy G. Froelich &amp; William M. Duckworth
Year:
2010
Abstract:
This article shows that when applying resampling methods to the problem of comparing two proportions, students can discover that whether you resample with or without replacement can make a big difference.
• ### Using research projects to help develop high school students' statistical thinking

Author(s):
Groth, R. E., Powell, N. N.
Year:
2004
Abstract:
This article describes two projects in which we attempted to help Advanced Placement (AP) statistics students become proficient at moving through the investigative cycle. Although the projects were implemented in an AP class, they could be included as part of any class in which linear equations and best-fit lines are studied. As we describe the two projects, we also discuss some of our reflections on the extent to which the projects helped our students become more proficient. In the first project, the students focused on the data analysis and inference phases. In the second project, the students had the opportunity to experience all phases of the cycle.
• ### Using Simple Linear Regression to Assess the Success of the Montreal Protocol in Reducing Atmospheric Chlorofluorocarbons

Author(s):
Dean Nelson
Year:
2009
Abstract:
Following the Guidelines for Assessment and Instruction in Statistics Education (GAISE) recommendation to use real data, an example is presented in which simple linear regression is used to evaluate the effect of the Montreal Protocol on atmospheric concentration of chlorofluorocarbons. This simple set of data, obtained from a public archive, can be used to tell a compelling story of success in international diplomacy solving a global environmental problem. A description of the use of these data and analyses are presented for a number of courses in applied statistics including introductory statistics.

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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