To determine significant causation requires an ANOVA an 'analysis of variance' between the groups to determine if there is causation. Remember, correlation does not equal causation. Neither of these tell you if one variable causes the variation in the other, though. A correlation of 0 (or near 0) indicates that there is very little relationship between variables. Correlation calculations result in a number between -1 and 1 with -1 and 1 being absolute relationship (the two variables move exactly proportionately to each other). Correlationis slightly stronger than covariance because it tells how strongly related two variables are. Variables can move in the same direction (positive covariance) or in opposite directions (negative covariance). You may remember that covarianceis a statistical calculation that results in either a positive or negative number indicating in what direction two variables move in relation to each other. Using Excel For Correlation, Covariance & ANOVA ฤก.
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