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

Constantin Anghelache and Sacala Cristina ()
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Constantin Anghelache: Bucharest University of Economic Studies, “ARTIFEX” University of Bucharest

Romanian Statistical Review Supplement, 2016, vol. 64, issue 9, 94-99

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.

Keywords: regression; correlation; intercept; variables (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (3)

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