Statistics Course Research Articles

Perceptions of attitudes toward statistics among medical undergraduates: insights from a regional medical college in China.

Among Chinese medical students, medical statistics is often perceived as a formidable subject. While existing research has explored the attitudes of Chinese postgraduate medical students towards statistics and its impact on academic performance, there is a scarcity of studies examining the attitudes of Chinese medical undergraduates on this subject. This study endeavors to scrutinize the attitudes of Chinese medical undergraduates towards statistics, assessing their ramifications on learning achievements, and delving into the influence of demographic factors. 1266 medical undergraduates participated in this study, completing a questionnaire that included SATS-36 and additional queries. Furthermore, an examination was administered at the end of the medical statistics course. The analysis encompassed the SATS score and exam scores, examining both the overall participant population and specific demographic subgroups. Undergraduate medical students generally exhibit a favorable disposition towards statistics concerning Affect, Cognitive Competence, and Value components, yet harbor less favorable sentiments regarding the Difficulty component of SATS-36, aligning with previous research findings. In comparison to their postgraduate counterparts, undergraduates display heightened enthusiasm for medical statistics. However, they demonstrate a lower cognitive capacity in statistics and tend to underestimate both the value and difficulty of learning statistics. Despite these disparities, undergraduate medical students express a genuine interest in statistics and exhibit a strong dedication to mastering the subject. It is noteworthy that students' attitudes toward statistics may be influenced by their major and gender. Additionally, there exists a statistically significant positive correlation between learning achievement and the Affect, Cognitive Competence, Value, Interest, and Effort components of the SATS-36, while a negative correlation is observed with the Difficulty component. Educators should carefully consider the influence of attitudes toward statistics, especially the variations observed among majors and genders when formulating strategies and curricula to enhance medical statistics education.

Postsecondary students’ understanding of statistics through story-based tasks

This paper is based on a study that explored a pedagogical approach consisting of interactive story-based tasks used in a first-year undergraduate business statistics course. It addresses the types of understanding students developed for selected statistics topics. Participants were undergraduate business majors required to take the course. Data consisted of the students’ work with the four story-based tasks. Findings suggest that interactive story-based tasks have the potential to be a worthwhile pedagogical approach to support students’ understanding of several statistics concepts at various levels of understanding, but further research is needed to better understand the pedagogical approach needed for adult learners to better implement these tasks to support the deepest level of understanding for all concepts.

Innovative Research on Curriculum Reform in the Context of Four New Discipline Construction -- Taking Probability Theory and Mathematical Statistics Course as an Example

With the massive emergence of new technologies empowered by big data and technology, the four original disciplines of engineering, agriculture, medicine and liberal arts have to keep up with the times and integrate big data, artificial intelligence and other related contents. New engineering, new agriculture, new medicine and new liberal arts came into being, the four new disciplines focus on professional cross-cutting practical [1], but also to improve the quality of talent training creative exploration, in the near future the layout of higher education disciplines or a major reshuffle will come. Industrial transformation and upgrading in the context of the national development of the economy is often heard by us, people need to study, digest, reform and innovate their own technology system on the basis of the introduction of advanced technology. Similarly the transformation and upgrading of disciplines in the context of the big data era is also imperative, various disciplines will develop in the direction of convergence and intersection, and disciplines can no longer be siloed disciplines, they all need to cross-fertilise with new big data-related knowledge to keep up with the times. Probability Theory and Mathematical Statistics is one of the required courses for undergraduates of statistics, big data and computer science majors, which are all related engineering and science majors under the construction of new engineering disciplines, while computers, the Internet, and artificial intelligence are driving educational changes and innovations, so the probability theory and mathematical statistics course should be integrated into the theories of the new engineering discipline to carry out innovation and reform. Through the restructuring of the teaching content to add the big data background of some of the methods to deal with the problem, so that students can use the idea of statistical modelling to analyze the economic and social stochastic phenomena, and can develop a pragmatic spirit based on data [3]. This paper will be from the reform of the teaching mode, teaching content innovation and restructuring, reform of the assessment method and the promotion of the four aspects of the teaching model to develop the probability theory and mathematical statistics in the four new disciplines under the background of the reform and innovation of the curriculum research.

Development of Electronic Test Instruments Through Vinesa to Improve Statistical Reasoning Ability on Tendency Central Materials

This study aims to assess the feasibility of developing an e-test instrument for statistics courses on central tendency material so that student learning outcomes can increase. The analysis used in this research is quantitative and descriptive. This research method uses 20 students. Methods of data collection using tests, observations, interviews, and questionnaires The procedures carried out in developing the test instrument are: 1) compiling test specifications; 2) writing test questions; 3) reviewing the item items; 4) conducting test trials; 5) analyzing the item items; 6) revising the test; 7) compiling the test; 8) carrying out the test; and 9) interpreting the test results. The ADDIE model is used in this development research. The results of the feasibility of developing electronic test instruments were stated to be valid with: a) the results of validating the material were very feasible (96%); b) the results of validating learning media were very feasible (94%). If c) the results of validating learning designs were very feasible (94%), d) the results of individual trials were very feasible (81%), and e) the results of small group trials were very feasible (82%), then the development of electronic test instruments is very feasible for use in statistical learning.

Student perceptions of weekly synchronous team quizzes in an online statistics course

In a fully online college introductory statistics class, we incorporated a flexible synchronous course component to provide instructor immediacy and support students who are lacking sufficient prior knowledge when a new topic is introduced. We describe a learning cycle with weekly team quizzes inspired by the readiness assurance process of team-based learning; we interviewed eight students for their perceptions of the course structure. Team quizzes are designed to provide regular formative assessment and feedback in real-time with the goal of improving student satisfaction and success in the course. Overall, students reported that the weekly synchronous sessions contributed to a strong sense of belonging to peers and the instructor, were helpful for their learning and helped them successfully complete the course. Implications for practice or policy: Instructors can use regular synchronous team quizzes in a fully online course to improve student engagement, connectedness, persistence and learning. Instructors can use team quizzes for regular formative assessment and feedback and to facilitate just-in-time intervention.

A Short Note on Generating a Random Sample from Finite Mixture Distributions

Computational statistics is a critical skill for professionals in fields such as data science, statistics, and related disciplines. One essential aspect of computational statistics is the ability to simulate random variables from specified probability distributions. Commonly employed techniques for sampling random variables include the inverse transform method, acceptance–rejection method, and Box–Muller transformation, all of which rely on sampling from the uniform (0,1) distribution. A significant concept in statistics is the finite mixture model, characterized by a convex combination of multiple probability density functions. In this paper, we introduce a modified version of the composition method, a standard approach for sampling finite mixture models. Our modification offers the advantage of relying on sampling from the uniform (0,1) distribution, aligning with prevalent methods in computational statistics. This alignment simplifies teaching computational statistics courses, as well as having other benefits. We offer several examples to illustrate the approach.

Changes in Undergraduate Students’ Self-Efficacy and Outcome Expectancy in an Introductory Statistics Course

The exploration of psychological variables that potentially impact college student performance in challenging academic courses can be useful for understanding success in introductory statistics. Although previous research has examined specific beliefs that students hold about their abilities and future outcomes, the current study is novel in its examination of changes in both self-efficacy (SE) and outcome expectancy (OE) in relation to performance over the course of an undergraduate introductory psychology statistics course. These psychological variables—relating to one’s belief about one’s ability to accomplish a task and the anticipated outcomes—may impact student motivation and performance. Students’ SE, OE, and other variables related to statistics performance were measured through a survey administered at the beginning and end of the course. Multivariate logistic regression and McNemar tests were conducted to examine factors that affected changes in SE and OE as the semester progressed. Students with lower scores on the final exam demonstrated a decrease in both high SE and positive OE. However, higher scores on exams earlier in the course were associated with increased odds for high SE but not for positive OE, suggesting that SE is less resilient to course performance. Based on these findings, the authors recommend that statistics instructors identify students at risk for decreasing SE. Instructors can help foster high SE in students struggling academically by connecting the course content to their everyday lives and suggesting strategies to enhance their confidence in their content knowledge and increase their comfort in navigating such a challenging course.

The Teaching of Introductory Statistics: Results of a National Survey

The Statistics Teaching Inventory (STI) was designed to assess the teaching practices of U.S.-based, college-level introductory statistics instructors in a variety of institutions and departments. This instrument has now been updated to reflect current trends and recommendations in statistics education. In this study, we used the STI to examine the current state of the curricular and instructional practices being used by U.S.-based, college-level introductory statistics instructors. We explore the extent to which instructors report that their introductory statistics courses are aligned with recommended practices as outlined by the 2016 GAISE College Report. Data were collected from a sample of college-level U.S.-based, college-level introductory statistics instructors. Results based on 228 usable responses indicated that instructors, by-and-large, tended to be following the GAISE recommendations, especially related to content. However, courses may not yet be aligned with newer content recommendations (e.g., provide students opportunities to work with multivariate data), and there is still a large percentage of instructors that are not embracing student-oriented pedagogies and assessment methods. Supplementary materials for this article are available online.

Diversifying Crime Datasets in Introductory Statistical Courses in Criminology

Diversifying Crime Datasets in Introductory Statistical Courses in Criminology

Learning From Online Instructional Videos Considering Video Presentation Modes, Technological Comfort, and Students Characteristics

Although much is known about the importance of video-based instruction for learning STEM online, how the instructor is presented in the video and how this impacts student reactions and learning remains largely under-explored, especially considering students’ backgrounds. Thus, we examined the relations between students’ backgrounds – specifically, comfort with technology and gender – and video presentation mode on learning from instructional STEM videos presented online. Using a mixed method design across two studies, we measured students’ accurate recall of STEM content, enjoyment, and attitude. Study 1 (n = 70) examined content from a computer programming course, and Study 2 (n = 60) replicated and expanded the first with content from a statistics course, and with additional videos and additional outcome measures. Results indicated that students’ comfort with technology was associated with learning outcomes, gender was sometimes associated with attitudes, but presentation mode did not impact outcomes. These studies have implications for course design, understanding and supporting student learning online, and future research.

Exploration of the Content Design and Assessment System of Statistics Course for Vocational Finance and Economics Majors Based on OBE

In the statistical teaching practice of various majors in economics and management in Chinese universities, there are generally drawbacks such as dull teaching content and weak applicability. How to organically integrate the teaching of statistical theory with practical teaching, and truly cultivate applied talents that meet the needs of regional economic and social development, is a prominent problem faced by the teaching of statistics courses in universities. This article aims to explore the content design and assessment system optimization of statistics courses in higher vocational finance and economics majors based on results oriented education. Through in-depth analysis of the connotation of OBE concept and its guiding significance for vocational education, combined with the characteristics of statistics in finance and economics majors, a series of course content design principles and assessment system reform suggestions are proposed to improve teaching quality, cultivate students' statistical application ability and innovative thinking.

Analysis of the Indonesian Version of the Statistical Anxiety Scale (SAS) Instrument with a Psychometric Approach

This study aims to validate the psychometric approach (using the RASCH Model and Confirmatory Factor Analysis) on the Indonesian version of the Statistical Anxiety Scale (SAS) instrument. Sampling in this study used cluster random sampling with a total sample of 1651 which was divided into 3 regions of Indonesia (Western Indonesia, Central Indonesia and Eastern Indonesia) with details of 457 males (27.46%) and 1194 females (72.54%). The number of samples from the West Indonesia region was 922 people (55.71%), the Central Indonesia region was 605 people (36.76%), and the Eastern Indonesia region was 124 people (7.53%). The results of the factor analysis (CFA) show that the dimensions/elements of the SAS instrument meet the criteria which are then continued using the Rating Scale Model (RSM) approach. From the results of the tests performed, it shows that all items on the Statistical Anxiety Scale (SAS) instrument meet the specified criteria. Thus, the SAS instrument adopted in the Indonesian context can be used to measure students' statistical anxiety. The results of the research conducted became the initial capital to increase students' statistical anxiety considering that statistics courses are needed in completing studies, especially quantitative research.

Experimentation on stochastic trajectories: From Brownian motion to inertial confined dynamics

Statistical physics courses typically employ abstract language that describes objects too small to be seen, making the topic challenging for students to understand. In this work, we introduce a simple experiment that allows conceptualizing some of the underlying ideas of stochastic processes through direct experimentation. Students analyze stochastic trajectories of beads in a bouncing bed of smaller beads subjected to an external periodic drive. The analysis of the trajectories involves the application of a vast toolkit of statistical estimators that are useful in many fields of physics.

Analısıs Kebutuhan Handout Bagı Mahasıswa Mbkm Untuk Mata Kulıah Statıstık Pendıdıkan SD

This research aims to determine the extent to which students taking part in the MBKM program need handouts for educational statistics course material. This type of research is qualitative descriptive research. The research subjects were 30 PGSD students in semester V and semester VII. The results of the comprehension test showed that of the 13 Course Learning Outcomes (CPMK), only 3 CPMK were understood by MBKM students well with results of more than 60%, namely basics of statistics (83.33%), data presentation (67%) and measurement. central symptoms (67%). Interview analysis, of the 5 Graduate Learning Outcomes (CPL) that must be met, almost every CPL student experiences difficulties in realizing the CPL in the MBKM activities they participate in. Based on the results of comprehension tests and interviews conducted, MBKM students need handouts as a companion in carrying out activities. It is hoped that students can use this handout to understand the material independently and continue to follow MBKM activities well.

Developing University Students’ Statistical Reasoning via a Research-informed Course

Statistical reasoning (SR) is an essential skill for students in studying statistics. This study aims to develop SR for university students through an appropriately designed course in statistics. Employing a quasi-experimental design, this study evaluated students' SR changes as they participated in a research-informed statistics course, designed to integrate statistical reasoning. The results showed that the course helps students improve their SR, with their scores increased by 23% from the pre-test to the post-test. Specifically, the SR scores on measures of central tendency of the experimental class increased by 8%; while the SR scores on the measures of variability of the experimental class increased by 34%. Suggestions about curriculum and teaching are included, such as offering opportunities for statistical investigations with real data; going deeper into building and understanding formulas; and training lecturers to teach statistics using approaches that are different from traditional teaching methods, as well as evaluating students' statistical learning with reliable tools.

Building Capacity for COVID-19 Surveillance: A Statistics Course for Health Officials in Seven Low- and Middle-Income Countries

During the COVID-19 pandemic, a group of health program implementors and research analysts across seven low- and middle-income countries (LMICs) alongside Boston-based collaborators convened to implement data-driven approaches for public health response. An intensive statistics and data science training short course was developed to ensure that in-country researchers could implement the necessary statistical methods for COVID-19 surveillance. The main goal of the course was to enable interpretation of findings from time series analyses and flag potential data issues. This manuscript summarizes our experience teaching this course, including a detailed course overview, participant feedback, and thoughts on how targeted, online courses can be used to support statistical capacity building in LMICs.

The useful and not so paradoxical inspection paradox

We offer ways that the inspection paradox can be usefully presented, even in the most elementary statistics courses, and provide guidance about how it can be revisited subsequently in the same course and in succeeding courses. Numerous situations in which the inspection paradox might occur are mentioned, and mathematically simple demonstrations are furnished in order to help convince students of the paradox’s veracity. Although remedial actions for the paradox are given, the main point of view is that the two sampling procedures leading to this apparent paradox are simply alternative methods that yield differing, but bona fide, measures and interpretations for the populations from which the data were obtained. Suggestions for student projects and undergraduate research are given.

Using Formative Assessment and Feedback from Student Response Systems (SRS) to Revise Statistics Instruction and Promote Student Growth for All

Instructors are increasingly using interactive student response systems (SRS) to foster active learning and deepen student understanding in statistics education. Yet most studies focus on either the benefits of SRS or on how students can receive and use feedback, rather than on how instructors can use formative assessment data to inform instructional revisions for the purpose of enacting inclusive pedagogy to reach more learners. This article draws from a case study of an introductory statistics course at a community college to detail a framework for how an instructor can engage in what I call a reciprocal formative assessment and feedback cycle using SRS. This cycle is designed to address the goal of increasing equity—as defined by learning growth for all students—through a structured approach of reflecting on student misconceptions to determine who to reteach, what to reteach, when to reteach, and how to reteach course content.

Diversifying Crime Datasets in Introductory Statistical Courses in Criminology

Contemporary criminology issues are increasingly global, cross-cultural, and multilingual. Moreover, students from different cultural and national backgrounds will need to apply data analytics in their respective contexts. Crime data used in statistical courses should reflect this diversity, and in turn enhance the equality and inclusivity of the teaching curriculum. Supported by evidence-based pedagogic principles and evaluations, researchers have identified strategies to enhance the teaching and learning of quantitative skills. Promoting students’ understanding of quantitative methods and their application in criminology requires that teaching materials reflect real-world problems and the diversity of today’s student population. To facilitate this aim, the article first describes over 40 open and accessible crime data sources across political, cultural, and linguistic borders in the Global South. Moreover, to support educators in their implementation and use of these datasets, the article presents three case studies of exemplar pedagogic activities using available data sources in an undergraduate Criminology program in the UK. Exemplar activities include (1) time series analysis of homicide in Asia; (2) bivariate analysis of trust in police and victimization in Algeria; and (3) mapping kidnappings in Mexico. We end by discussing the pedagogical and research implications of diversifying datasets and some future challenges.

Teaching Reform of “Probability Theory and Mathematical Statistics” Under the Background of New Engineering

Probability theory and mathematical statistics are fundamental courses for various majors in science and engineering. In response to the current teaching situation, we should integrate theory with practice, implement teaching reform, and carry out teaching innovation. The article carries out blended teaching with deep integration of online and offline modes and within and outside of class, constructing innovative measures of “four integrations and four reshaping.” The article conducts diversified evaluations to stimulate learning motivation and help achieve talent cultivation goals. Through the close integration of probability theory and mathematical statistics course teaching with professional education and practical application, the “three-in-one” teaching goal of value shaping, ability cultivation, and knowledge exploration is achieved. The fundamental task of “cultivating morality and talents” is implemented.