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Conceptual understanding of linear regression among economics students at the university center of Tipaza, Algeria

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  • Idris Djouahra

    (Centre Universitaire de Tipaza, Algeria)

Abstract

Solving problems related to econometrics requires a good knowledge of regression analysis concepts. The objective of this study is to evaluate students’ difficulties resulting from the lack of knowledge of regression analysis concepts among economics students enrolled in the Master’s cycle at the institute of economics at the university center of Tipaza (Algeria). In order to analyze students’ answers, a typical correction was prepared based on professors’ answers to this questionnaire. The procedure consists of comparing students’ key answers with their corresponding typical answers to see how near or far it is from the right answer. In order to see whether the difficulties are originated from the same students, we analyzed the association between answers based on Multiple Correspondence Analysis (MCA) method. The principal results showed that difficulties resulting from the lack of knowledge of regression analysis concepts were prevalent among students. Their main causes were strongly related to misunderstanding, misconceptions and confusions. MCA analysis indicated that students can be categorized according to their answers into four groups: a very weak group, a weak group, an average group and a good group. We concluded that the difficulty of solving problems in the context of linear regression among students is the result of a lack of knowledge of regression concepts coupled with the inability to explain them.

Suggested Citation

  • Idris Djouahra, 2022. "Conceptual understanding of linear regression among economics students at the university center of Tipaza, Algeria," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 8(2), pages 66-83, December.
    • Handle: RePEc:vrs:crebss:v:8:y:2022:i:2:p:66-83:n:2
    DOI: 10.2478/crebss-2022-0011
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    References listed on IDEAS

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    1. Joshua D. Angrist & Jörn-Steffen Pischke, 2017. "Undergraduate Econometrics Instruction: Through Our Classes, Darkly," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 125-144, Spring.
    2. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    3. Spanos,Aris, 1986. "Statistical Foundations of Econometric Modelling," Cambridge Books, Cambridge University Press, number 9780521269124.
    4. Thomas Lindner & Jonas Puck & Alain Verbeke, 2020. "Misconceptions about multicollinearity in international business research: Identification, consequences, and remedies," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 51(3), pages 283-298, April.
    5. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    6. G. M. Peter Swann, 2019. "Is precise econometrics an illusion?," The Journal of Economic Education, Taylor & Francis Journals, vol. 50(4), pages 343-355, October.
    7. C. J. Wild & M. Pfannkuch, 1999. "Statistical Thinking in Empirical Enquiry," International Statistical Review, International Statistical Institute, vol. 67(3), pages 223-248, December.
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    More about this item

    Keywords

    conceptual understanding; econometrics; economics; linear regression;
    All these keywords.

    JEL classification:

    • A20 - General Economics and Teaching - - Economic Education and Teaching of Economics - - - General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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