Attitudes towards Statistics among Business Students: Do Gender, Mathematical Skills and Personal Traits Matter?

Abstract

The purpose of this article was to investigate different variables, by combining mathematical skills and personal traits using The Big Five Model, to see which have the most influence on business students’ attitudes towards statistics. The Big Five personality traits make up a model for capturing various personal characteristics. Specifically, we aimed to understand why there is a gender difference in attitudes towards statistics. Statistical skills are a key factor for success in business studies. The chosen methods were pairwise comparisons (t-test) and a linear regression model, using a sample from a Norwegian business school. The finding was that there is a substantial gender gap towards attitudes towards statistics but taking mathematical skills and personal characteristics into consideration then results in this gap becoming much smaller. Furthermore, mathematical skills and personal traits were shown to have an impact on students’ attitudes towards statistics.

Un modelo bifactor para la Escala de Actitudes hacia la Estadística

“…En la muestra sin ponderar, los datos apoyan la hipótesis de no diferencia entre sexos (Comas et al, 2017;Pérez et al, 2015;Salinas & Mayén, 2016;Sarikaya et al, 2018). Sin embargo, los datos de la muestra ponderada por semestre apoyan la hipótesis de diferencia con mayor seguridad y una actitud más positiva en hombres que en mujeres (Auzmendi, 1991;Hommik & Luik, 2017;Opstad, 2020;Rejón-Guardia et al 2019), siendo el tamaño del efecto del sexo medio sobre la seguridad y pequeño sobre la actitud general. La muestra sin ponderar está sesgada por una mayor participación de los alumnos de los primeros semestres.…”

“…Se espera una actitud polarizada hacia la aceptación (Bautista et al, 2016;Comas et al, 2017). Las expectativas con respecto a las diferencias en los niveles actitudinales promedios entre ambos sexos no son claras, ya que los resultados de los estudios varían de no diferencia (Comas et al, 2017;Pérez et al, 2015;Salinas & Mayén, 2016;Sarikaya et al, 2018) a mayor promedio en hombres 1991;Hommik & Luik, 2017;Rejón-Guardia et al, 2019;Opstad, 2020) o mayor promedio en mujeres (Mahmud & Zainol, 2008). La hipótesis de validez concurrente es que exista una correlación positiva y alta entre la actitud hacia la estadística y la actitud hacia la investigación (Baños & Hurtado, 2016).…”

Attitudinal changes in face-to-face and online statistical reasoning learning environments

“…Another study conducted across three years of an introductory statistics course at Cornell University (n = 611) found no significant differences by race in average SATS-28 subscales scores, but did find that females reported significantly lower Affect and Cognitive Competence averages than their male counterparts, despite the fact that the instructor for all sections was female ( van Es & Weaver, 2018). Opstad (2020) found somewhat different results when administering the SATS-36 to a sample of 140 business students enrolled in a macroeconomics course. In his study, males and females reported similar scores on Affect and Cognitive Competence, although the males did find statistics more interesting, more valuable, and easier than the females.…”

Motivation for Learning Mathematics: A Study Across Disciplines

“…Conversely, they created video related to engineering which apply mathematics skills in order to help the students foresee the applications. On the other hand, research from Opstad (2020) showed that female students from business discipline had a harder time learning statistics and needed to put in a lot more effort compared to male students. Having difficulties in Mathematics will eventually decrease the motivation to learn that subject matter as well as affect their achievement.…”