Correlation
1. Shows strength of association between two variables
2. Tells us how much the two variables are associated with each other
3. However, does not assume CAUSATION
4. Simply tells us whether the two variables are positively or negatively correlated
Regression
If there is a strong correlation between two variables, Regr
ession is used to determine Y (dependent variable) from the X's (Independent variables on which Y depends)Types of regressions: Linear, Multiple...
You use Coefficient of Correlation (r) as to measure the strength of relationships between two variables
r is also called Pearson's Coefficient.
r can range from -1 to +1
Values of -1 or
+1 indicate strong correlation (-1 perfect negative relationship (inverse relationship) and +1 perfect positive correlation)Values close to 0.0 indicate weak correlation
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