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50 Years of ERIC
50 Years of ERIC
The Education Resources Information Center (ERIC) is celebrating its 50th Birthday! First opened on May 15th, 1964 ERIC continues the long tradition of ongoing innovation and enhancement.

Learn more about the history of ERIC here. PDF icon

Showing all 5 results
Kozak, Marcin; Wnuk, Agnieszka – Teaching Statistics: An International Journal for Teachers, 2014
The Tukey mean-difference plot, also called the Bland-Altman plot, is a recognized graphical tool in the exploration of biometrical data. We show that this technique deserves a place on an introductory statistics course by encouraging students to think about the kind of graph they wish to create, rather than just creating the default graph for the…
Descriptors: Statistics, Graphs, Introductory Courses, Mathematics Instruction
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Kozak, Marcin – Teaching Statistics: An International Journal for Teachers, 2011
This article addresses an important problem of graphing quantitative data: should one include zero on the scale showing magnitude? Based on a real time series example, the problem is discussed and some recommendations are proposed.
Descriptors: Graphs, Data, Statistics, Mathematical Concepts
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Kozak, Marcin – Teaching Statistics: An International Journal for Teachers, 2010
Asterisks should not be used to indicate if the result of a hypothesis test is significant.
Descriptors: Hypothesis Testing, Statistics, Mathematical Concepts, Mathematics Instruction
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Kozak, Marcin – Teaching Statistics: An International Journal for Teachers, 2009
This article suggests how to explain a problem of small sample size when considering correlation between two Normal variables. Two techniques are shown: one based on graphs and the other on simulation. (Contains 3 figures and 1 table.)
Descriptors: Sample Size, Correlation, Predictor Variables, Simulation
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Kozak, Marcin – Teaching Statistics: An International Journal for Teachers, 2009
Interpretation of correlation is often based on rules of thumb in which some boundary values are given to help decide whether correlation is non-important, weak, strong or very strong. This article shows that such rules of thumb may do more harm than good, and instead of supporting interpretation of correlation--which is their aim--they teach a…
Descriptors: Correlation, Misconceptions, Statistics, Mathematical Concepts