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Variyath, Asokan Mulayath; Nadarajah, Tharshanna – Teaching Statistics: An International Journal for Teachers, 2022
Undergraduate statistics teaching has always faced the challenge of improving the learning quality on a continuous basis. Interactive statistical applets can enhance statistical knowledge by providing multiple representations of basic concepts and facilitating experimentation. The use of these applets will simplify the efforts for teaching…
Descriptors: Learning Processes, Statistics Education, Educational Technology, Undergraduate Students
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Chen, Lin-An; Kao, Chu-Lan Michael – International Journal of Mathematical Education in Science and Technology, 2022
The uniformly most accurate (UMA) is an important optimal approach in interval estimation, but the current literature often introduces it in a confusing way, rendering the learning, teaching and researching of UMA problematic. Two major aspects cause this confusion. First, UMA is often interpreted to maximize the accuracy of coverage, but in fact,…
Descriptors: Accuracy, Mathematics Instruction, Learning Processes, Probability
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Allison S. Theobold; Megan H. Wickstrom; Stacey A. Hancock – Journal of Statistics and Data Science Education, 2024
Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…
Descriptors: Computer Science Education, Coding, Data Science, Statistics Education
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Johnson, Marina E.; Misra, Ram; Berenson, Mark – Decision Sciences Journal of Innovative Education, 2022
In the era of artificial intelligence (AI), big data (BD), and digital transformation (DT), analytics students should gain the ability to solve business problems by integrating various methods. This teaching brief illustrates how two such methods--Bayesian analysis and Markov chains--can be combined to enhance student learning using the Analytics…
Descriptors: Bayesian Statistics, Programming Languages, Artificial Intelligence, Data Analysis
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Scheller, Daniel S. – Journal of Public Affairs Education, 2022
The general growth in public affairs programs offering hybrid and online courses to reach a wide variety of students, along with the necessity of doing so during a global health pandemic, calls for an investigation of best practices in teaching public affairs statistics and research-oriented courses. These courses often require the use of a…
Descriptors: Case Studies, Programming Languages, Statistics Education, Teaching Methods
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Zadeh, Amir H.; Zolbanin, Hamed M.; Sharda, Ramesh – Journal of Information Systems Education, 2021
The age of big data drives the need for emerging technologies to enable scalable analytics on massive, rapidly generated, and varied data. It requires "data scientists" with deep knowledge of managing the six Vs of big data: volume, velocity, variety, volatility, veracity, and value. As a result of this trend, new analytical tools are…
Descriptors: Social Media, Business Administration Education, Data Analysis, Teaching Methods
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Mix, Kelly S.; Smith, Linda B.; Crespo, Sandra – Research in Mathematics Education, 2019
In this chapter, we focus on the difficulties children face when learning place value and how current psychological theories of relational learning may be leveraged by teachers. We discuss two major psychological mechanisms known to support relational learning--statistical learning and structure mapping--and review the evidence showing how these…
Descriptors: Mathematics Instruction, Instructional Improvement, Statistics Education, Difficulty Level