Abstract:

The subject of Econometrics is a core subject in most of the studies related to the Economy. Students of Econometrics often have a poor grounding in mathematics which generally leads them to have a negative tendency towards Econometrics. The lack of confidence in the understanding of the concepts leads to a concern about how to pass the subject and the existence of a high percentage of students not having the right implication in the study of matter.

From a simple viewpoint, the lack of implication of the students with econometrics could be prompted by the high mathematical contents, which in the most of cases are abstract for the students. However, if we analyze this question in depth, it is clear that there are others factors which directly affect the disposition that the students have towards the subject. For this reason, during the academic year 2011/2012, we the teachers involved in such matters decided to try to find what factors have a positive and negative influence to overcoming it. With this objective, we have put together an empirical study of students in the fifth grade of the Administration and Business and Law double degree, using a questionnaire. From the data obtained in the questionnaire, we have described an econometric model which we will be using to estimate the score of a student considering the corresponding explanatory variables, among others, overcoming the retake subjects of Mathematics and Quantitative Techniques, the average number of weekly hours devoted to studying and the average number of weekly attendance hours.

The proposed econometric model will allow us to conclude which variables, among all employees, are significant or insignificant on the expected score and its level of influence on the dependent variable. As a final objective, an on-going pursuit of what factors should be strengthened to enhance the learning and understanding of the subject "Econometrics" towards making the student feel more comfortable in a setting that facilitates the overcoming of matter.

Keywords:

Econometric, Expected score, Linear Regression.