Business Statistics Course Research Articles

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.

THE ROLE OF SCIENTIFIC CALCULATORS IN IMPROVING STATISTICS LEARNING

In its development, Business Statistics has used several types of technology to facilitate the learning process for students, such as statistical software, spreadsheets, calculators, multimedia materials, and data repositories. The calculator includes computer technology with a simple version but allows students to experience an active learning process. Thus, the calculator media was chosen as the main learning media in business statistics courses, including in evaluating student abilities. Therefore, this study aims to determine the effectiveness of using calculators in Business Statistics courses. The research was conducted using a mix method, namely qualitative (questionnaire) and quantitative (experimental). The results showed that there was an increase in the average value of Simple Linear Regression for groups of students who used statistical applications on calculators compared to groups who did not use calculators. Based on the results of the questionnaire and suggestions, it was found that 87.7% of students considered it easy to understand the Business Statistics application questions, when using the statistical application on a calculator. Suggestions made by students were the availability of guidelines for using statistical calculator applications for practice, and the availability of calculators in the research laboratory that students could use for practice

Can Gender and Major Explain College Students’ Performance in Business Statistics?

Recent discussions in education, industry, and government have focused on the need for growth and diversity in STEM fields. STEM education and practice directly contribute to the economic vitality of a nation and benefit its citizens. Yet, STEM education and employment growth seem lopsided concerning both gender and diversity. While researchers have studied various dimensions of this phenomenon, this paper seeks to add to the knowledge base by analyzing the effects of gender and college major on performance and attitudes in statistics-related courses. T-tests, one-way analysis of variance, and multiple regression were used to investigate the effects of gender, major, and attitude on performance in business statistics courses. Results indicate that, in the business statistics course, there were no significant differences between the average score of male students and female students in 2 of 3 semesters. In the marketing research course, where similar statistical concepts as taught in the business statistics course were adopted, results were similar. However, there were differences in the students’ scores when their academic majors were considered. Findings from this study can contribute to developing effective and innovative pedagogical methodologies to teach statistics and related subjects.

Teaching reform and practice of Business Statistics course based on motivating students to learn

This paper focuses on the concept of "student-centered" in response to the guidelines put forward by the Ministry of Education on undergraduate teaching, and the design of the teaching objectives, teaching process and teaching assessment based on the analysis of the learning situation and the reinforcement theory on how to motivate students. The course "Business Statistics" has carried out a series of explorations and practices to stimulate students' learning motivation, and the overall attendance rate and average score of students have been improved to a certain extent, and students' evaluation scores of teachers' teaching have also been improved, achieving good results.

Online Teaching Quality Evaluation of Business Statistics Course Utilizing Fermatean Fuzzy Analytical Hierarchy Process with Aggregation Operator

Due to the full-scale outbreak of COVID-19, many universities have adopted the way of online teaching to ensure the orderly development of teaching plans and teaching contents. However, whether online and offline teaching can develop homogeneously and how to ensure the teaching effect is a major challenge for colleges and universities. Therefore, it is urgent to construct a reasonable index system and evaluation approach for the quality of network teaching. Combined with the influencing factors and characteristics of online teaching, this study first puts forward a multi-index evaluation index system and then proposes a novel evaluation method for online teaching based on the analytical hierarchy process (AHP) and Dombi weighted partitioned Muirhead Mean (PMM) operator under Fermatean fuzzy (FF) environment. This presented method not only adapts to changeable evaluation information but also handles the elusive interrelationships among indexes, realizing the flexibility and comprehensiveness both in form and in the polyaddition process. The applicability and feasibility of this presented method are then discussed through the practical online teaching quality evaluation of a business statistics course case, and a group of tentative about the sensitivity analysis and comparative analysis further demonstrates the effectiveness and flexibility of the proposed method.

How Are Students Learning in a Business Statistics Course? Evidence from Both Direct and Indirect Assessment

This paper studies how both direct and indirect assessment outcomes can determine how students are learning different concepts in business statistics. We explore connections between the outcomes from the two assessment approaches and how different student characteristics and background factors impact these two methods of assessment. The results based on a sample of 64 students enrolled in an undergraduate business statistics course at a large public university designated as a minority-serving institution show some similarities and some differences among the two types of assessment outcomes and the insights they provide about overall student learning in the course. Furthermore, factors like gender and background grade point average are seen to impact both direct and indirect assessment results, whereas others such as the type of business concentration and student status only impact one type of assessment. Finally, we show that some indirect assessment outcomes can predict direct assessment outcomes while controlling for demographic and other background variables.

EVALUATING THE IMPACT OF WORKED EXAMPLE VIDEOS FOR BLENDED LEARNING IN A LARGE-ENROLMENT BUSINESS STATISTICS COURSE

Statistics courses are frequently perceived by tertiary students as extremely difficult and anxiety-inducing, negatively impacting student outcomes and experiences. To address this, the present study considered worked example videos (where an instructor demonstrates the solution to a problem while narrating the process) as a blended learning approach for enhancing an introductory business statistics course taken by 2265 students over three semesters. Impact was evaluated with video usage, academic performance, and student survey data. Students heavily utilised worked example videos before assessment deadlines, frequently employing active learning strategies during their engagements. Improvements in academic performance and course satisfaction were observed compared to previous cohorts. This demonstrates worked example videos are well-suited to large-enrolment courses due to their highly scalable capacity to deliver timely support for learning, which individuals can tailor to their diverse needs.

Forecasting Students’ Final Exam: Results Using Multiple Regression Analysis in an Undergraduate Business Statistics Course

This paper discusses the development of a multiple regression model to predict the final examination marks of students in an undergraduate business statistics course. The marks of a sample of 366 students in the Winter 2017 semester were used to fit the regression model. The final model contained three predictor variables namely two test marks and the homework assignment mark. The marks of another 194 students from Winter 2018 were used to validate the model. The model validation showed that it can be used for future cohorts of students for prediction. The two main objectives of the study were to use the model as a teaching tool in class and to use the model to predict final examination marks of future students.

Efektivitas Hybrid Method (Metode TMa dan IK) pada Pembelajaran Daring untuk Mata Kuliah Statistik

The purpose of this study was to determine the effectiveness of the hybrid learning method (hybrid method) in economic and business statistics courses. The research method uses a mixed method between a quantitative approach and a qualitative approach using primary data. The data were tested using one of the different test analyzes, namely the Paired-Samples T Test. The findings indicate that an effective hybrid method is used for classes of economic statistics and business. Students prefer to use the IK method combined with the TMa (virtual face) method because they can understand the material quickly and the method is very similar to conventional methods. The theoretical implication of this research is that the hybrid method is better used for online learning methods than the IK method. Meanwhile, the practical implication in this study is that teachers can use the hybrid method for mathematics-based and calculation-based courses because the results of the study show that computation-based statistics courses can be effectively implemented using the hybrid method.

Causal inference in the presence of missing data using a random forest‐based matching algorithm

Observational studies require matching across groups over multiple confounding variables. Across the literature, matching algorithms fail to handle the issue of missing data. Consequently, missing values are regularly imputed prior to being considered in the matching process. However, imputing is not always practical, forcing us to drop an observation due to the deficiency of the chosen algorithm, decreasing the power of the study and possibly failing to capture crucial latent information. We propose a missing data mechanism to incorporate within an iterative multivariate matching method. The underlying framework utilizes random forest as a natural tool in constructing a distance matrix, implemented with surrogate splits where there might be missing values. The output is then easily fed into an optimal matching algorithm. We apply this method to evaluate the effectiveness of supplemental instruction (SI) sessions, a voluntary program where students seek additional help, in a large enrollment, bottleneck introductory business statistics course. This is an observational study with two groups, those who attend multiple SI sessions and those who do not, and, as typical in educational data mining, challenged by missing data. Additionally, we perform a data simulation on missingness to further demonstrate the efficacy of our proposed approach.

Efektifitas Pembelajaran Melalui Media Daring Ditinjau Dari Hasil Belajar Mahasiswa Pada Masa Pandemi Covid 19

Coronavirus disease 2019 (Covid-19) outbreak that has hit 215 countries in the world, presents its own challenges for educational institutions, especially universities. To fight Covid-19, the government has banned universities from carrying out face-to-face (conventional) lectures and ordered to hold lectures or learning online. Whatsapp Group is one of the familiar and frequently used distance learning media. While Zoom Meeting application is a learning media using video so that it more resembles a face-to-face meeting. This study aims to see the effectiveness of Advanced Business Statistics learning by using Whatsapp Group media and Zoom Meeting application reviewed from student learning outcomes at STIE Bisnis Indonesia Solutions. This type of research is a quasi experiment using one group pretest-postest design. The sample of research is 4th semester students who took advanced business statistics courses as many as 100 people. Sample data is processed with descriptive analysis and average difference test using Wilcoxon Signed Rank Test and N-Gain Score. The results showed that Advanced Business Statistics Course Lecture at STIE Solusi Bisnis Indonesia using WhatsApp Group media and Zoom Meeting application is not effective when viewed from student learning results. This can be seen in the N-Gain value obtained a result of 0.16.

A Web-based Matrix Organizer for Chunked Multimedia Course Content

This study presents a web-based matrix organizer that houses multi-media course content, including videos and infographics, for an undergraduate business statistics course. Content is “chunked” into microlessons explaining the “When, What and How” of several statistical techniques. An observational study was conducted to evaluate satisfaction with the tool and how the tool influenced learning. Results show that students felt the tool was easy to use and helped them organize and learn information. Some evidence suggests users have higher perceived learning and grades than non-users. The structure can be used for other courses; recommendations for implementing similar systems are presented.

Teaching Business Statistics: Some Useful Relationships

The purpose of this paper is to suggest an instructional approach in the introductory business statistics course that utilizes relationships between separately introduced topics. The paper will explore three “useful relationships” that can assist classroom instruction: (1) the relationship between the simple arithmetic mean, the weighted arithmetic mean, and the expected value of a discrete probability distribution; (2) the relationship between the use of the multiplication rule to calculate the joint probability associated with two events, use of tree diagrams, and the use of the binomial and hypergeometric distributions; and (3) the relationship between the geometric mean and the compound interest rate. Each discussion includes detailed examples of calculations to demonstrate the relationships.

Exploring the Roles of Social Presence and Gender Difference in Online Learning

ABSTRACTOnline learning has become more popular in higher education with its advantages of flexibility and accessibility. However, there have been challenges to students’ learning experience in online learning. One critical challenge would be providing interactions between students and instructors as good or effective as in the face‐to‐face environment. However, providing face‐to‐face interactions in online learning is not feasible because students and instructors are not physically present together. In this study, we introduce and empirically investigate social presence as student learning experience in online learning in which physical presence does not exist. Drawing upon the social presence and online learning literature, we propose a research model to explore how the interactivity of communication tools can drive social presence and student satisfaction in online learning. Furthermore, this study examines gender difference as a moderator in the model. Data were collected from undergraduate students who were taking online business statistics courses where an interactive communication tool was required to use for class communication and collaboration. The results showed that social presence driven by tool interactivity had a significant impact on student satisfaction in online learning. We also found that gender difference moderated the relationship between tool interactivity and social presence in online learning.

Improving Student Performance in an Undergraduate Business Statistics Course Using Technology Enhanced Learning

Improving Student Performance in an Undergraduate Business Statistics Course Using Technology Enhanced Learning

The effect of cognitive and behavioral factors on student success in a bottleneck business statistics course via deeper analytics

In this article, we study a set of factors underlying student success in a bottleneck business course using statistical and data mining techniques. Factors included learning styles, motivational and other cognitive factors, personality traits, learning analytics, along with background demographic and academic ones. Our analysis yielded interesting insights that show some of these factors play significant roles in predicting both student performance and their propensity to utilize resources that help improve their performance, such as additional support services. The predictive accuracy of both of our models were over 95% (error rate <5%). Moreover, quantile regression models were used to determine factors that specifically affect the performance of low-performing students so that targeted intervention and support services can be developed specifically for them. In conclusion, deeper analytics via statistical models are crucial for forming an in-depth understanding of how to improve student performance in a bottleneck course and this has far-reaching implications for both educators and administrators in higher education.

Some Suggestions for Teaching Undergraduate Business Statistics Courses

Student anxiety is high in many business statistics courses. Often, students fail in these courses because they rely highly on grades rather than on meaningful learning. Instructors also feel the pressure because their students do not attempt to learn deeply. I taught Quantitative Methods courses for a number of years in a University in Ontario, Canada. In this paper, I have critically analyzed some of the challenges that instructors face in teaching these courses and suggested some solutions based on an educational point of view. Continuous assessment, portfolio construction, and improving the efficiency of instructor evaluations are three key suggestions for consideration.&#x0D; As these challenges are common to most undergraduate courses in business statistics, the suggestions would mainly help to raise student motivation, encourage students to learn deeply, and increase instructor efficiency.

Dual Mode Delivery in an Introductory Statistics Course: Design and Evaluation

In recent years, the Australian tertiary education sector embraced the gradual adaption of the dual mode system in course delivery in universities and higher degree education providers. In such systems, students have the option, as well as the flexibility, to undertake the same course in a face-to-face (F2F) environment and/or an online environment. This article presents an evaluation of the dual mode design of a first-year business statistics course delivered at the Griffith University. In this article, we discuss the various aspects of the dual mode design in the course, emphasizing the use of consistent teaching strategies for the F2F and online student cohorts. Moreover, we present a comparative analysis of learning satisfaction and academic performance of the two cohorts within the dual mode system. Using t-tests, nonparametric tests, and propensity score matching estimators we provide new insights into dual mode course design. Our results suggest no significant difference in student experiences and outcomes. Discussion and analysis presented in this article is useful as feedback for further improvement in teaching strategies in the delivery of dual mode courses.

A geometric approach to multicollinearity

URL: http://users.dickinson.edu/∼erfle/ExcelGraphics/Multicollinearity.xlsxInstructors teaching empirical techniques in managerial economics or economic and business statistics courses often face a...

Using the Occupational Information Network (O*NET) to demonstrate the importance of understanding statistics for undergraduate students

SummaryBecause of the increasing use of business analytics to improve business processes, it is not difficult to argue the importance that undergraduate business students gain the ability to understand, interpret, and communicate statistics. However, a task that may be difficult for statistics instructors is to quickly demonstrate and convince business students the importance of statistics. This paper presents an assignment that utilizes the Occupational Information Network (O*NET) to demonstrate the importance of understanding basic statistical concepts such as population parameters, sampling methods, descriptive measures, and displaying data. This can be administered to an introductory business statistics course in order to drum up students' initial interest and views of applicability of statistics.