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Q. Explain Correlation Coefficient?
Ans.
The strength of a linear correlation is determined by how precisely the y variable shifts as the x variable increases. The two pictures on the right show data with a higher correlation than those on the left.
Data is said to have a perfect correlation if all points lie exactly along a line.
The correlation coefficient, r, is a measure of the strength of the correlation. It is a number between 1 and +1. +1 indicates a perfect positive correlation and 1 indicated a perfect negative correlation. If r is positive, then there is a positive correlation between the two variables. If r is negative, there is a negative correlation between the variables.
The dataset also contains a variable y , which is the dependent variable of interest, as well as x1 , x2 , x3 , x4 , x5 , and x6 , all explanatory variables that are potentially
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