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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 1 to 15 of 96 results
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Wulff, Shaun S.; Robinson, Timothy J. – Journal of Statistics Education, 2014
Bayesian methodology continues to be widely used in statistical applications. As a result, it is increasingly important to introduce students to Bayesian thinking at early stages in their mathematics and statistics education. While many students in upper level probability courses can recite the differences in the Frequentist and Bayesian…
Descriptors: Bayesian Statistics, Probability, College Mathematics, Mathematics Instruction
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Kaplan, Jennifer J.; Gabrosek, John G.; Curtiss, Phyllis; Malone, Chris – Journal of Statistics Education, 2014
Histograms are adept at revealing the distribution of data values, especially the shape of the distribution and any outlier values. They are included in introductory statistics texts, research methods texts, and in the popular press, yet students often have difficulty interpreting the information conveyed by a histogram. This research identifies…
Descriptors: Statistical Distributions, Graphs, Undergraduate Students, Misconceptions
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Satake, Eiki; Murray, Amy Vashlishan – Journal of Statistics Education, 2014
Although Bayesian methodology has become a powerful approach for describing uncertainty, it has largely been avoided in undergraduate statistics education. Here we demonstrate that one can present Bayes' Rule in the classroom through a hypothetical, yet realistic, legal scenario designed to spur the interests of students in introductory- and…
Descriptors: Bayesian Statistics, College Mathematics, Mathematics Instruction, Statistics
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Dunn, Peter K. – Journal of Statistics Education, 2013
In this paper, we report a case study that illustrates the importance in interpreting the results from statistical tests, and shows the difference between practical importance and statistical significance. This case study presents three sets of data concerning the performance of two brands of batteries. The data are easy to describe and…
Descriptors: Equipment, Performance, Statistical Analysis, Statistical Significance
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Doehler, Kirsten; Taylor, Laura; Smith, Jessalyn – Journal of Statistics Education, 2013
The purpose of this research is to better understand the role of statistics in teaching and research by faculty from all disciplines and their perceptions of the statistical preparation of their students. This study reports the findings of a survey administered to faculty from seven colleges and universities regarding the use of statistics in…
Descriptors: Statistics, College Faculty, College Instruction, Student Research
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Schneiter, Kady; Symanzik, Jurgen – Journal of Statistics Education, 2013
This article describes an applet that facilitates investigation of Simpson's Paradox in the context of a number of real and hypothetical data sets. The applet builds on the Baker-Kramer graphical representation for Simpson's Paradox. The implementation and use of the applet are explained. This is followed by a description of how the…
Descriptors: Computer Oriented Programs, Computer Uses in Education, Statistics, Visual Aids
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Wroughton, Jacqueline; Cole, Tarah – Journal of Statistics Education, 2013
Recognizing the differences between three discrete distributions (Binomial, Hypergeometric and Negative Binomial) can be challenging for students. We present an activity designed to help students differentiate among these distributions. In addition, we present assessment results in the form of pre- and post-tests that were designed to assess the…
Descriptors: Statistics, Mathematics Instruction, Active Learning, Mathematical Concepts
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Gonul, Fusun F.; Solano, Roger A. – Journal of Statistics Education, 2013
We investigate business undergraduate mathematics-based courses in a blended environment of online assignments and exams and offline lectures, and report the impact on academic performance of factors such as classroom attendance, web-based course supplements, and homework. We present results from both ordinary least squares and fixed effects,…
Descriptors: Computer Assisted Instruction, Business Administration Education, Mathematics Instruction, College Mathematics
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Witt, Gary – Journal of Statistics Education, 2013
This paper shows how the application of simple statistical methods can reveal to students important insights from climate data. While the popular press is filled with contradictory opinions about climate science, teachers can encourage students to use introductory-level statistics to analyze data for themselves on this important issue in public…
Descriptors: Climate, Data, Introductory Courses, Statistics
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Leemis, Lawrence M.; Luckett, Daniel J.; Powell, Austin G.; Vermeer, Peter E. – Journal of Statistics Education, 2012
We describe a web-based interactive graphic that can be used as a resource in introductory classes in mathematical statistics. This interactive graphic presents 76 common univariate distributions and gives details on (a) various features of the distribution such as the functional form of the probability density function and cumulative distribution…
Descriptors: Probability, Statistical Distributions, Transformations (Mathematics), Bayesian Statistics
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Phelps, Amy L. – Journal of Statistics Education, 2012
Service-learning can mean different things and look quite different in varying statistics curricula that may include undergraduates, graduates, majors and non-majors across a wide array of higher institutions. The terms community engagement, volunteerism, community-based projects and service-learning are tossed around on various institutions'…
Descriptors: Service Learning, Statistics, College Mathematics, Mathematics Instruction
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Braun, W. John – Journal of Statistics Education, 2012
The Analysis of Variance is often taught in introductory statistics courses, but it is not clear that students really understand the method. This is because the derivation of the test statistic and p-value requires a relatively sophisticated mathematical background which may not be well-remembered or understood. Thus, the essential concept behind…
Descriptors: Statistical Analysis, Visual Aids, Mathematics Instruction, Introductory Courses
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Burks, Robert E.; Jaye, Michael J. – Journal of Statistics Education, 2012
The "Price Is Right" ("TPIR") provides a wealth of material for studying statistics at various levels of mathematical sophistication. The authors have used elements of this show to motivate students from undergraduate probability and statistics courses to graduate level executive management courses. The material consistently generates a high…
Descriptors: Learner Engagement, Probability, Statistics, Mathematics Instruction
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Perrett, Jamis J. – Journal of Statistics Education, 2012
This article demonstrates how textbooks differ in their description of the term "experimental unit". Advanced Placement Statistics teachers and students are often limited in their statistical knowledge by the information presented in their classroom textbook. Definitions and descriptions differ among textbooks as well as among different editions…
Descriptors: Statistics, Advanced Placement Programs, Textbooks, Mathematics Instruction
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Tishkovskaya, Svetlana; Lancaster, Gillian A. – Journal of Statistics Education, 2012
Over the past few decades there has been a large amount of research dedicated to the teaching of statistics. The impact of this research has started to change course content and structure, in both introductory and advanced courses for statisticians and those from other disciplines. In the light of these changes future directions in the teaching…
Descriptors: Statistics, Mathematics Instruction, College Instruction, Educational Change
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