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Multiple linear regression used to analyse the corelation between GDP and some variables

Author

Listed:
  • Constantin Anghelache

    (Bucharest University of Economic Studies, “ARTIFEX” University of Bucharest)

  • Cristina SACALÃ

    (Bucharest University of Economic Studies)

Abstract

Statistical researchers often use a linear relationship to predict the (average) numerical value of Y for a given value of X using a straight line (called the regression line). If you know the slope and the y-intercept of that regression line, then you can plug in a value for X and predict the average value for Y. In other words, you predict (the average) Y from X. If you establish at least a moderate correlation between X and Y through both a correlation coefficient and a scatterplot, then you know they have some type of linear relationship.

Suggested Citation

  • Constantin Anghelache & Cristina SACALÃ, 2016. "Multiple linear regression used to analyse the corelation between GDP and some variables," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(9), pages 94-99, September.
    • Handle: RePEc:rsr:supplm:v:64:y:2016:i:9:p:94-99
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. 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.
    3. Madalina-Gabriela ANGHEL & Radu STOICA & Tudor SAMSON & Alexandru BADIU, 2017. "Analysis of the Econometric model of the correlation between GDP and final consumption," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(2), pages 122-129, February.

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