Which of the following correlation coefficients may represent a strong correlation? (2024)

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Which of the following correlation coefficients may represent a strong correlation? ›

Generally, correlation coefficients range between -1.00 to +1.00. According to the rule of correlation coefficients, the strongest correlation is considered when the value is closest to +1 (positive correlation) or -1 (negative correlation).

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.

If the correlation coefficient is greater than zero, it is a positive relationship. Conversely, if the value is less than zero, it is a negative relationship. A value of zero indicates that there is no relationship between the two variables.

Out of the given correlation coefficients, +. 80 represents the strongest relationship between two variables. It indicates a robust positive correlation, meaning that as one variable increases, the other typically increases as well, and vice versa.

Correlation coefficients whose magnitude are between 0.7 and 0.9 indicate variables which can be considered highly correlated. Correlation coefficients whose magnitude are between 0.5 and 0.7 indicate variables which can be considered moderately correlated.

The correlation coefficient of 0.2 before excluding outliers is considered as negligible correlation while 0.3 after excluding outliers may be interpreted as weak positive correlation (Table 1).

The strength of the correlation is indicated by the by number of the r, meaning the absolute number, whether negative or positive.

A Pearson correlation coefficient of 0.5 indicates a moderate positive correlation. More generally, a correlation coefficient between 0.4 and 0.7 is usually considered a moderate correlation.

What is a weak or strong correlation? ›

What is strong or weak correlation? - Quora. A correlation with a magnitude close to -1 (negative correlation) or +1 (positive correlation) indicates a strong correlation or linear relationship. Whereas, a correlation equal to 0 or near 0 indicates practically no linear relationship or weak 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.

Examples of positive correlations occur in most people's daily lives. The more hours an employee works, for instance, the larger that employee's paycheck will be at the end of the week. The more money is spent on advertising, the more customers buy from the company.

In statistics, correlation refers to the measure of the relationship between two sets of data. A strong positive correlation means that as one variable increases, the other variable also increases, while a strong negative correlation means that as one variable increases, the other variable decreases.

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.

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.

For this kind of data, we generally consider correlations above 0.4 to be relatively strong; correlations between 0.2 and 0.4 are moderate, and those below 0.2 are considered weak.

The magnitude of the correlation coefficient indicates the strength of the association. For example, a correlation of r = 0.9 suggests a strong, positive association between two variables, whereas a correlation of r = -0.2 suggest a weak, negative association.