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Nobuyuki Hanaki; Jan R. Magnus; Donghoon Yoo – Journal of Statistics and Data Science Education, 2023
Common sense is a dynamic concept and it is natural that our (statistical) common sense lags behind the development of statistical science. What is not so easy to understand is why common sense lags behind as much as it does. We conduct a survey among Japanese students and provide examples and tentative explanations of a number of statistical…
Descriptors: Statistics, Statistics Education, Epistemology, Statistical Analysis
Sinharay, Sandip – Grantee Submission, 2021
Drasgow, Levine, and Zickar (1996) suggested a statistic based on the Neyman-Pearson lemma (e.g., Lehmann & Romano, 2005, p. 60) for detecting preknowledge on a known set of items. The statistic is a special case of the optimal appropriateness indices of Levine and Drasgow (1988) and is the most powerful statistic for detecting item…
Descriptors: Robustness (Statistics), Hypothesis Testing, Statistics, Test Items
Liu, Lu; Haque, M. D. – Online Journal of Distance Learning Administration, 2017
This study identified the moderated mediation relationship among age, Internet self-efficacy, and statistics anxiety on student satisfaction after controlling for demographics and technology experiences in research methods courses in a blended professional doctoral program. One hundred and thirty-one students in a three-year Ed.D. Program…
Descriptors: Graduate Students, Student Research, Methods Courses, Blended Learning
Rashid, Mamunur; Sarkar, Jyotirmoy – Educational Research Quarterly, 2018
Students in an online statistics course were prone to become increasingly disengaged as the semester progressed. In Spring 2015, we took a proactive measure to retain student engagement by introducing a cyber mentoring session. We describe the framework, operation and effectiveness of cyber mentoring in improving students' learning experience and…
Descriptors: Online Courses, Statistics, Educational Technology, Technology Uses in Education
Zimmerman, Whitney Alicia; Johnson, Glenn – Online Learning, 2017
Data were collected from 353 online undergraduate introductory statistics students at the beginning of a semester using the Goals and Outcomes Associated with Learning Statistics (GOALS) instrument and an abbreviated form of the Statistics Anxiety Rating Scale (STARS). Data included a survey of expected grade, expected time commitment, and the…
Descriptors: Undergraduate Students, Statistics, Online Courses, Academic Persistence
Vaughan, Timothy S. – Journal of Statistics Education, 2015
This paper introduces a dataset and associated analysis of the scores of National Football League (NFL) games over the 2012, 2013, and first five weeks of the 2014 season. In the face of current media attention to "lopsided" scores in Thursday night games in the early part of the 2014 season, t-test results indicate no statistically…
Descriptors: Team Sports, Success, Scores, Statistics
Mogro-Wilson, Cristina; Reeves, Michael G.; Charter, Mollie Lazar – Journal of Teaching in Social Work, 2015
This article describes the development of two doctoral-level multivariate statistics courses utilizing sociocultural theory, an integrative pedagogical framework. In the first course, the implementation of sociocultural theory helps to support the students through a rigorous introduction to statistics. The second course involves students…
Descriptors: Social Work, Graduate Students, Doctoral Programs, Sociocultural Patterns
McCulloch, Ryan Sterling – International Journal of Higher Education, 2017
The role of any statistics course is to increase the understanding and comprehension of statistical concepts and those goals can be achieved via both theoretical instruction and statistical software training. However, many introductory courses either forego advanced software usage, or leave its use to the student as a peripheral activity. The…
Descriptors: Statistics, Mathematics Instruction, Introductory Courses, Computer Software
Chamberlain, John Martyn; Hillier, John; Signoretta, Paola – Active Learning in Higher Education, 2015
This article reports the results of research concerned with students' statistical anxiety and confidence to both complete and learn to complete statistical tasks. Data were collected at the beginning and end of a quantitative method statistics module. Students recognised the value of numeracy skills but felt they were not necessarily relevant for…
Descriptors: Anxiety, Statistical Analysis, Student Attitudes, Statistics
Nielson, Perpetua Lynne; Bean, Nathan William Bean; Larsen, Ross Allen Andrew – Statistics Education Research Journal, 2018
We examine the impact of a flipped classroom model of learning on student performance and satisfaction in a large undergraduate introductory statistics class. Two professors each taught a lecture-section and a flipped-class section. Using MANCOVA, a linear combination of final exam scores, average quiz scores, and course ratings was compared for…
Descriptors: Educational Technology, Technology Uses in Education, Homework, Video Technology
Curran-Everett, Douglas – Advances in Physiology Education, 2012
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This eighth installment of "Explorations in Statistics" explores permutation methods, empiric procedures we can use to assess an experimental result--to test a null hypothesis--when we are reluctant to trust statistical…
Descriptors: Statistical Analysis, Statistics, Physiology, Research Methodology
Williams, Amanda – Journal of Statistics Education, 2014
The purpose of the current research was to investigate the relationship between preference for numerical information (PNI), math self-concept, and six types of statistics anxiety in an attempt to establish support for the nomological validity of the PNI. Correlations indicate that four types of statistics anxiety were strongly related to PNI, and…
Descriptors: Correlation, Preferences, Self Concept, Mathematics Skills
Olinsky, Alan; Schumacher, Phyllis; Quinn, John – International Journal for Mathematics Teaching and Learning, 2012
In this paper, we discuss the importance of teaching power considerations in statistical hypothesis testing. Statistical power analysis determines the ability of a study to detect a meaningful effect size, where the effect size is the difference between the hypothesized value of the population parameter under the null hypothesis and the true value…
Descriptors: Testing, Sample Size, Hypothesis Testing, Statistics
Schraw, Gregory; Kuch, Fred; Gutierrez, Antonio P.; Richmond, Aaron S. – Journal of Educational Psychology, 2014
We compared 5 different statistics (i.e., G index, gamma, "d'", sensitivity, specificity) used in the social sciences and medical diagnosis literatures to assess calibration accuracy in order to examine the relationship among them and to explore whether one statistic provided a best fitting general measure of accuracy. College…
Descriptors: Statistics, Statistical Analysis, Correlation, Accuracy
Schlotter, Nicholas E. – Journal of Chemical Education, 2013
Our ability to statistically analyze data has grown significantly with the maturing of computer hardware and software. However, the evolution of our statistics capabilities has taken place without a corresponding evolution in the curriculum for the undergraduate chemistry major. Most faculty understands the need for a statistical educational…
Descriptors: Statistics, College Mathematics, College Science, Undergraduate Students

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