Title: Exploring students’ flaws and errors when interpreting linear regression models
Abstact: Linear regression models are applied in multiple disciplines on a daily basis. Still, the results produced by the modelling are being misinterpreted even in cross-validated publications. When building statistical knowledge, it is important to observe and correct the misconceptions in the early stages of statistic studies, as it is more difficult to correct them later. In this study, the flaws and errors were categorized based on statistics basic course students’ interpretations of linear regression models in the course's final exam. The focus was on flaws and errors made when interpreting the linear regression model results such as regression coefficients and statistical significance.
