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The multiple linear regression used to analyse the correlation between variables

Author

Listed:
  • Dan CRUCERU

    („ARTIFEX” University of Bucharest)

  • Madalina Gabriela ANGHEL

    („ARTIFEX” University of Bucharest)

  • Aurelian DIACONU

    („ARTIFEX” University of Bucharest)

Abstract

The use of the statistical-econometric models in macro-economic analyses can be used successfully by using the model of simple linear regression but, multiple linear regression is preffered because more factors influence the evolution of resultative variables. In the case of multiple linear regression we have to identify the factors we consider and they should be included in the reconexed model, following the same graphic representation, of establishing the corelograma to make the inventory of the cloud of dots and the evolution of each variable, and based on that we may interprete the data and moreover, based on the value of the regression parameters, we may identify the intensity, direction of influence, in other words, the intensity of the correlation between the considered factors.

Suggested Citation

  • Dan CRUCERU & Madalina Gabriela ANGHEL & Aurelian DIACONU, 2016. "The multiple linear regression used to analyse the correlation between variables," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(10), pages 114-117, October.
    • Handle: RePEc:rsr:supplm:v:64:y:2016:i:10:p:114-117
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    References listed on IDEAS

    as
    1. Bruce A. Blonigen & Ronald B. Davies & Glen R. Waddell & Helen T. Naughton, 2019. "FDI in Space: Spatial Autoregressive Relationships in Foreign Direct Investment," World Scientific Book Chapters, in: Foreign Direct Investment, chapter 2, pages 55-88, World Scientific Publishing Co. Pte. Ltd..
    2. Emilian Dobrescu, 2013. "Updating the Romanian Economic Macromodel," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-31, December.
    3. Constantin ANGHELACHE & Madalina Gabriela ANGHEL & Ligia PRODAN & Cristina SACALA & Marius POPOVICI, 2014. "Multiple Linear Regression Model Used in Economic Analyses," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 62(10), pages 120-127, Octomber.
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    Cited by:

    1. Constantin Anghelache & Aurelian DIACONU & Andreea Ioana MARINESCU & Marius POPOVICI, 2016. "Comparative study of the evolution of the Gross Domestic Product indicator," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(12), pages 165-172, December.
    2. Constantin ANGHELACHE & Ion PARTACHI & Madalina-Gabriela ANGHEL & Gyorgy BODO & Radu STOIAN, 2016. "General theoretical notions on univariate regression," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(11), pages 136-144, November.

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