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Rebeka Man – ProQuest LLC, 2024
In today's era of large-scale data, academic institutions, businesses, and government agencies are increasingly faced with heterogeneous datasets. Consequently, there is a growing need to develop effective methods for extracting meaningful insights from this type of data. Quantile, expectile, and expected shortfall regression methods offer useful…
Descriptors: Data, Data Analysis, Data Use, Higher Education
Jule Scheper; Robin Leuppert; Daniel Possler; Anna Freytag; Sophie Bruns; Julia Niemann-Lenz – Journalism and Mass Communication Educator, 2025
Despite the increasing use of the statistical programming language R in statistics and data analysis (SDA), its implementation in communication science education is limited. Experiences, recommendations, and a critical exchange are therefore scarce. The following contribution addresses this very gap. At the Department of Journalism and…
Descriptors: Journalism Education, Programming Languages, Statistical Analysis, Data Analysis
Joseph Chiarelli; Melissa A. St. Hilaire; Brandi L. Baldock; Jimmy Franco; Stephen Theberge; Anthony L. Fernandez – Journal of Chemical Education, 2025
There is a growing need for chemistry students to be able to handle and manipulate large datasets and analyze them in an efficient and accessible way. This creates the need to develop course materials that introduce these topics early in the undergraduate curriculum. To address this growing need, this activity introduced RStudio to students…
Descriptors: Chemistry, Science Instruction, College Science, Undergraduate Students
Jeremy L. Hsu; Sara Gartland; Joelle Prate; Charles Hohensee – CBE - Life Sciences Education, 2025
Quantitative reasoning (QR) is a key skill for undergraduate biology education. Despite this, many students struggle with QR. Here, we use the theoretical framework of student noticing to investigate why some students struggle with QR in introductory biology labs. Under this framework, what students notice when given new information and data…
Descriptors: Thinking Skills, Numeracy, Introductory Courses, Biology
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
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
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
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
McFadden, Rory R.; Viskupic, Karen; Egger, Anne E. – Journal of Geoscience Education, 2021
Quantitative literacy is a foundational component of success in STEM disciplines and in life. Quantitative concepts and data-rich activities in undergraduate geoscience courses can strengthen geoscience majors' understanding of geologic phenomena and prepare them for future careers and graduate school, and provide real-world context to apply…
Descriptors: Earth Science, College Science, College Faculty, Mathematics Skills
Jones, Thomas J.; Ehlers, Todd A. – Journal of Geoscience Education, 2021
The need for geoscience students to develop a quantitative skillset is ever increasing. However, this can be difficult to implement in university-style lecture courses in a way that is both manageable for the instructor and does not involve lengthy, potentially repetitive, question sheets for the students. Here, a method for teaching dimensional…
Descriptors: Earth Science, Science Experiments, Graduate Students, College Science
Cominole, Melissa; Ritchie, Nichole Smith; Cooney, Jennifer – National Center for Education Statistics, 2021
This publication describes the methods and procedures used for the 2008/18 Baccalaureate and Beyond Longitudinal Study (B&B:08/18). The B&B graduates, who completed the requirements for a bachelor's degree during the 2007-08 academic year, were first surveyed as part of the 2008 National Postsecondary Student Aid Study (NPSAS:08), and then…
Descriptors: Bachelors Degrees, College Graduates, Longitudinal Studies, Data Collection
Abdulkadir Palanci; Rabia Meryem Yilmaz; Zeynep Turan – Education and Information Technologies, 2024
This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…
Descriptors: Learning Analytics, Distance Education, Educational Trends, Periodicals
Albers, Michael J. – Journal of Technical Writing and Communication, 2017
A quantitative research study collects numerical data that must be analyzed to help draw the study's conclusions. Teaching quantitative data analysis is not teaching number crunching, but teaching a way of critical thinking for how to analyze the data. The goal of data analysis is to reveal the underlying patterns, trends, and relationships of a…
Descriptors: Statistical Analysis, Data Analysis, College Curriculum, Graduate Study
Zane, Len – Honors in Practice, 2020
Many of the numbers used to assess students are statistical in nature. The theoretical context underlying the production of a typical number or statistic used in student assessment is presented. The author urges readers to recognize objective data as subjective information and to carefully consider the numbers that often determine admission,…
Descriptors: Student Evaluation, Statistical Analysis, Honors Curriculum, Admission Criteria
He, Lingjun; Levine, Richard A.; Fan, Juanjuan; Beemer, Joshua; Stronach, Jeanne – Practical Assessment, Research & Evaluation, 2018
In institutional research, modern data mining approaches are seldom considered to address predictive analytics problems. The goal of this paper is to highlight the advantages of tree-based machine learning algorithms over classic (logistic) regression methods for data-informed decision making in higher education problems, and stress the success of…
Descriptors: Institutional Research, Regression (Statistics), Statistical Analysis, Data Analysis