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Which of the Following Would Not Be a Correct Interpretation of a Correlation of R = .90

Correlation is a statistical measure that determines the relationship between two variables. It tells us how strong and in what direction the relationship is. The correlation coefficient, denoted by “r,” ranges from -1 to 1. A perfect positive correlation is represented by 1, indicating that both variables move in the same direction. Conversely, a perfect negative correlation is represented by -1, indicating that the variables move in opposite directions. When the correlation coefficient is close to 0, it suggests no relationship between the variables.

In this article, we aim to discuss the interpretation of a correlation coefficient of R = .90 and identify which of the following interpretations would not be correct. Let’s delve into the possibilities and explore their validity.

Interpretation 1: There is a strong positive relationship between the variables.

A correlation coefficient of R = .90 indicates a strong positive relationship between the variables being analyzed. This means that as one variable increases, the other variable is likely to increase as well. This interpretation is correct, as a correlation coefficient of .90 is considered very high.

Interpretation 2: The variables are perfectly correlated.

A correlation coefficient of R = .90 does not indicate a perfect correlation. As mentioned earlier, a perfect correlation is represented by a coefficient of 1. While .90 is close to 1, it still falls short of a perfect correlation. Therefore, this interpretation would not be correct.

Interpretation 3: The variables have a weak relationship.

With a correlation coefficient of R = .90, it is incorrect to state that the variables have a weak relationship. A correlation coefficient above .70 is generally considered to be a strong relationship. Therefore, this interpretation would also be incorrect.

Interpretation 4: The correlation is negative.

A correlation coefficient of R = .90 implies a positive relationship between the variables. A negative correlation would be represented by a coefficient below 0. Therefore, this interpretation would not be correct.

Interpretation 5: The correlation is weak.

As mentioned earlier, a correlation coefficient of R = .90 suggests a strong relationship between the variables. Therefore, interpreting it as a weak correlation would be incorrect.

FAQs

Q: What does a correlation coefficient of .90 mean?

A: A correlation coefficient of .90 indicates a strong positive relationship between the variables being analyzed. As one variable increases, the other variable is likely to increase as well.

Q: Can a correlation coefficient be greater than 1?

A: No, a correlation coefficient cannot be greater than 1. The range of correlation coefficients is from -1 to 1, where -1 represents a perfect negative correlation, 1 represents a perfect positive correlation, and 0 represents no relationship between the variables.

Q: Is a correlation coefficient of .90 considered high?

A: Yes, a correlation coefficient of .90 is considered very high. It suggests a strong relationship between the variables.

Q: Can we conclude that one variable causes the other based on a correlation coefficient?

A: No, correlation does not imply causation. While a strong correlation suggests a relationship between variables, it does not necessarily mean that one variable causes the other. Other factors and variables may be involved, and further analysis is needed to establish causality.

In conclusion, a correlation coefficient of R = .90 signifies a strong positive relationship between the variables being analyzed. It is incorrect to interpret it as a perfect correlation, weak relationship, negative correlation, or weak correlation. Remember, correlation is a valuable statistical tool, but it does not indicate causation. It is essential to consider other factors and conduct further analysis to understand the relationship between variables more comprehensively.

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