Question

Can you explain the relationships among covariance, scatterplot, and correlation?

Answer 1

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Relationship between the three:

1. Covariance vs. Correlation

“Covariance” indicates the direction of the linear relationship between variables. “Correlation” measures both the strength and the direction of the linear relationship between two variables. Both these metrics , covariance and correlation, are terms to measure the relationship and the dependency between two variables.

Also, like correlation, Covariances measures only linear dependence.

2. Scatter plot vs Correlation vs Covariances:

Scatterplot are nothing but visualization for bivariate analysis to check the spatial distribution of 2 variables. They are used to check correlation between 2 variables. The relationship can be linear or non-linear. But if the relationship is linear we can comment on the strength and direction of correlation surely.

Therefore, like correlation and covariances, the following inferences can be made about scatter plot and covariances : Negative covariance corresponds to downward-sloping scatterplots (negative correlation). Positive covariance corresponds to upward-sloping scatterplots ( positive correlation).

Also, the more is the spread of the scatter plot, the lesser is the correlation, the lesser is the Covariance (dependency ) between the 2 variables. Vice-versa is also true i.e. Less the spread, more is the correlation, hence, more the Covariance.