So, why is correlation useful? Correlation can help in predicting one attribute from another (Great way to impute missing values). Correlation can (sometimes) indicate the presence of a causal relationship.

## Is a correlation of 0.4 good?

We can tell when the correlation is high because the data points hover closely to the line of best fit (seen in red). Generally, a value of r greater than 0.7 is considered a strong correlation. Anything between 0.5 and 0.7 is a moderate correlation, and anything less than 0.4 is considered a weak or no correlation.

## Is a correlation value of good?

The correlation coefficient is a statistical measure of the strength of the relationship between the relative movements of two variables. The values range between -1.0 and 1.0. A correlation of -1.0 shows a perfect negative correlation, while a correlation of 1.0 shows a perfect positive correlation.

## Why is correlation useful?

Not only can we measure this relationship but we can also use one variable to predict the other. For example, if we know how much were planning to increase our spend on advertising then we can use correlation to accurately predict what the increase in visitors to the website is likely to be.

## Is a correlation of 0.6 good?

Correlation Coefficient = +1: A perfect positive relationship. Correlation Coefficient = 0.8: A fairly strong positive relationship. Correlation Coefficient = 0.6: A moderate positive relationship.

## How much correlation is significant?

In most research the threshold to what we consider statistically significant is a p-value of 0.05 or below and its called the significance level α. So we can set our significance level to 0.05 (α =0.05) and find the P-value.

## Is 0.5 A strong correlation?

Correlation coefficients whose magnitude are between 0.5 and 0.7 indicate variables which can be considered moderately correlated. Correlation coefficients whose magnitude are between 0.3 and 0.5 indicate variables which have a low correlation.

## Is correlation useless?

Correlation (or any other measure of association) is useful for prediction regardless of causation. Suppose that you measure a clear, stable association between two variables.

## Is .25 a weak correlation?

25 or . 3 (weak correlations).

## Is 0.5 A weak correlation?

Correlation coefficients whose magnitude are between 0.5 and 0.7 indicate variables which can be considered moderately correlated. Correlation coefficients whose magnitude are between 0.3 and 0.5 indicate variables which have a low correlation.