Is 0.6 A strong correlation?
Correlation Coefficient = 0.8: A fairly strong positive relationship. Correlation Coefficient = 0.6: A moderate positive relationship.
Correlation coefficients whose magnitude are between 0.3 and 0.5 indicate variables which have a low correlation. Correlation coefficients whose magnitude are less than 0.3 have little if any (linear) correlation.
Positive correlation is measured on a 0.1 to 1.0 scale. Weak positive correlation would be in the range of 0.1 to 0.3, moderate positive correlation from 0.3 to 0.5, and strong positive correlation from 0.5 to 1.0. The stronger the positive correlation, the more likely the stocks are to move in the same direction.
For a natural/social/economics science student, a correlation coefficient higher than 0.6 is enough. Correlation coefficient values below 0.3 are considered to be weak; 0.3-0.7 are moderate; >0.7 are strong. You also have to compute the statistical significance of the correlation.
Values between 0.3 and 0.7 (-0.3 and -0.7) indicate a moderate positive (negative) linear relationship via a fuzzy-firm linear rule. Values between 0.7 and 1.0 (-0.7 and -1.0) indicate a strong positive (negative) linear relationship via a firm linear rule.
Strength of relationship
The correlation between two variables is considered to be strong if the absolute value of r is greater than 0.75.
Correlation Coefficient = 0.8: A fairly strong positive relationship. Correlation Coefficient = 0.6: A moderate positive relationship. Correlation Coefficient = 0: No relationship. As one value increases, there is no tendency for the other value to change in a specific direction.
The relationship between two variables is generally considered strong when their r value is larger than 0.7. The correlation r measures the strength of the linear relationship between two quantitative variables.
The sign of the linear correlation coefficient indicates the direction of the linear relationship between x and y. When r (the correlation coefficient) is near 1 or −1, the linear relationship is strong; when it is near 0, the linear relationship is weak.
High degree: If the coefficient value lies between ± 0.50 and ± 1, then it is said to be a strong correlation.
What is the minimum value of correlation?
The linear correlation coefficient, R, is a measure of the association between two variables. The maximum value for R is + 1. The minimum value for R is - 1. In both these cases, all sample points fall on a straight line.
A perfectly positive correlation means that 100% of the time, the variables in question move together by the exact same percentage and direction. A positive correlation can be seen between the demand for a product and the product's associated price.
Correlation is expressed on a range from +1 to -1, known as the correlation coefficent. In a perfect positive correlation, expressed as +1, an increase or decrease in one variable always predicts the same directional change for the second variable.
Generally, an R-Squared above 0.6 makes a model worth your attention, though there are other things to consider: Any field that attempts to predict human behaviour, such as psychology, typically has R-squared values lower than 0.5.
As a rule of thumb, a correlation coefficient between 0.25 and 0.5 is considered to be a “weak” correlation between two variables. 2. This rule of thumb can vary from field to field. For example, a much lower correlation could be considered weak in a medical field compared to a technology field.
This is interpreted as follows: a correlation value of 0.7 between two variables would indicate that a significant and positive relationship exists between the two.
So to answer your question: r close to 0 and p-value < 0.05 would mean that there is a correlation, but it is very weak.
As a rule of thumb, a correlation coefficient between 0.25 and 0.5 is considered to be a “weak” correlation between two variables. 2. This rule of thumb can vary from field to field. For example, a much lower correlation could be considered weak in a medical field compared to a technology field.
If we wish to label the strength of the association, for absolute values of r, 0-0.19 is regarded as very weak, 0.2-0.39 as weak, 0.40-0.59 as moderate, 0.6-0.79 as strong and 0.8-1 as very strong correlation, but these are rather arbitrary limits, and the context of the results should be considered.
The sign of the linear correlation coefficient indicates the direction of the linear relationship between x and y. When r (the correlation coefficient) is near 1 or −1, the linear relationship is strong; when it is near 0, the linear relationship is weak.
