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Matchett, Andrew – PRIMUS, 2023
This article describes five elementary statistics projects involving the COVID-19 data made available to the public in csv files by the Centers for Disease Control and Prevention. The first project examined data available at the beginning of the COVID surge in New York City in spring, 2020, and used the correlation coefficient to estimate the…
Descriptors: Statistics Education, Student Projects, COVID-19, Pandemics
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François, Karen; Monteiro, Carlos; Allo, Patrick – Statistics Education Research Journal, 2020
In the contemporary society a massive amount of data is generated continuously by various means, and they are called Big-Data sets. Big Data has potential and limits which need to be understood by statisticians and statistics consumers, therefore it is a challenge to develop Big-Data Literacy to support the needs of constructive, concerned, and…
Descriptors: Data Collection, Data Analysis, Statistical Analysis, Comprehension
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Changpetch, Pannapa; Reid, Moya – Journal of Education for Business, 2021
Based on a statistical analysis, undergraduate business students are shown to prefer classification tree over six other standard data mining techniques. Data were collected over a 4-year period from students taking a data mining course offered at a business university in the US. The principal reason given by students for this preference is that…
Descriptors: Data Analysis, Models, Statistical Analysis, Undergraduate Students
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Ferguson, Sarah L.; Moore, E. Whitney G.; Hull, Darrell M. – International Journal of Behavioral Development, 2020
The present guide provides a practical guide to conducting latent profile analysis (LPA) in the Mplus software system. This guide is intended for researchers familiar with some latent variable modeling but not LPA specifically. A general procedure for conducting LPA is provided in six steps: (a) data inspection, (b) iterative evaluation of models,…
Descriptors: Statistical Analysis, Computer Software, Data Analysis, Goodness of Fit
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Goretzko, David; Heumann, Christian; Bühner, Markus – Educational and Psychological Measurement, 2020
Exploratory factor analysis is a statistical method commonly used in psychological research to investigate latent variables and to develop questionnaires. Although such self-report questionnaires are prone to missing values, there is not much literature on this topic with regard to exploratory factor analysis--and especially the process of factor…
Descriptors: Factor Analysis, Data Analysis, Research Methodology, Psychological Studies
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Cheung, Mike W.-L. – Research Synthesis Methods, 2019
Meta-analysis and structural equation modeling (SEM) are 2 of the most prominent statistical techniques employed in the behavioral, medical, and social sciences. They each have their own well-established research communities, terminologies, statistical models, software packages, and journals ("Research Synthesis Methods" and…
Descriptors: Structural Equation Models, Meta Analysis, Statistical Analysis, Data Analysis
Mohammad, Nagham; McGivern, Lucinda – Online Submission, 2020
In regression analysis courses, there are many settings in which the response variable under study is continuous, strictly positive, and right skew. This type of response variable does not adhere to the normality assumptions underlying the traditional linear regression model, and accordingly may be analyzed using a generalized linear model…
Descriptors: Regression (Statistics), Statistical Distributions, Simulation, Data Analysis
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Simsek, Ahmet Salih – International Journal of Assessment Tools in Education, 2023
Likert-type item is the most popular response format for collecting data in social, educational, and psychological studies through scales or questionnaires. However, there is no consensus on whether parametric or non-parametric tests should be preferred when analyzing Likert-type data. This study examined the statistical power of parametric and…
Descriptors: Error of Measurement, Likert Scales, Nonparametric Statistics, Statistical Analysis
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Haardörfer, Regine – Health Education & Behavior, 2019
In this article, Regine Haardörfer outlines five general steps taken by good data analysts and how they need to be theory-driven data-informed. She uses these to discuss some issues and propose approaches to promote better data analysis and reporting. The proposed steps to rigorous data analysis are to: (1) create an a priori data analysis plan;…
Descriptors: Data Analysis, Theories, Social Science Research, Behavioral Science Research
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Burian, Alexis N.; Zhao, Wufan; Lo, Te-Wen; Thurtle-Schmidt, Deborah M. – Biochemistry and Molecular Biology Education, 2021
To fully appreciate genetics, one must understand the link between genotype (DNA sequence) and phenotype (observable characteristics). Advances in high-throughput genomic sequencing technologies and applications, so-called "-omics," have made genetic sequencing readily available across fields in biology from applications in…
Descriptors: Genetics, Science Instruction, Teaching Methods, Biology
Najib A. Mozahem – Sage Research Methods Cases, 2021
The internet has had a vast and pervasive effect on many industries. It has resulted in the creation of new industries and has overhauled the dynamics that governed existing industries. One of the most traditional industries that is now struggling to cope with the changes brought on by the internet is the industry of higher education. Students can…
Descriptors: Social Sciences, Electronic Learning, Learning Management Systems, Higher Education
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Bornn, Luke; Mortensen, Jacob; Ahrensmeier, Daria – Canadian Journal for the Scholarship of Teaching and Learning, 2022
This paper presents a novel design for an upper-level undergraduate statistics course structured around data rather than methods. The course is designed around curated datasets to reflect real-world data science practice and engages students in experiential and peer learning using the data science competition platform Kaggle. Peer learning is…
Descriptors: Undergraduate Study, Cooperative Learning, Peer Influence, Undergraduate Students
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Wind, Stefanie A. – Measurement: Interdisciplinary Research and Perspectives, 2020
A major challenge in the widespread application of Mokken scale analysis (MSA) to educational performance assessments is the requirement of complete data, where every rater rates every student. In this study, simulated and real data are used to demonstrate a method by which researchers and practitioners can apply MSA to incomplete rating designs.…
Descriptors: Item Response Theory, Scaling, Nonparametric Statistics, Performance Based Assessment
Cho, April E.; Wang, Chun; Zhang, Xue; Xu, Gongjun – Grantee Submission, 2020
Multidimensional Item Response Theory (MIRT) is widely used in assessment and evaluation of educational and psychological tests. It models the individual response patterns by specifying functional relationship between individuals' multiple latent traits and their responses to test items. One major challenge in parameter estimation in MIRT is that…
Descriptors: Item Response Theory, Mathematics, Statistical Inference, Maximum Likelihood Statistics
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Tanner, Sean; Terrell, Jenna; Vislosky, Emily; Gellar, Jonathan; Gill, Brian – Regional Educational Laboratory Mid-Atlantic, 2021
Predicting incoming enrollment is an ongoing concern for the School District of Philadelphia (SDP) and similar districts with school choice systems, substantial student mobility, or both. Inaccurate predictions can disrupt learning as districts adjust to enrollment fluctuations by reshuffling teachers and students well into the fall semester. This…
Descriptors: Enrollment, Enrollment Projections, School Districts, Statistical Analysis
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