# How do you interpret correlation?

## How do you interpret correlation?

A correlation of -1.0 indicates a perfect negative correlation, and a correlation of 1.0 indicates a perfect positive correlation. 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.

### What does correlation matrix tell us?

A correlation matrix is a table showing correlation coefficients between variables. Each cell in the table shows the correlation between two variables. A correlation matrix is used to summarize data, as an input into a more advanced analysis, and as a diagnostic for advanced analyses.

How much correlation is significant?

Values always range between -1 (strong negative relationship) and +1 (strong positive relationship). Values at or close to zero imply a weak or no linear relationship. Correlation coefficient values less than +0.8 or greater than -0.8 are not considered significant.

Is Pearson Correlation the p-value?

The Pearson correlation coefficient is a number between -1 and 1. The P-value is the probability that you would have found the current result if the correlation coefficient were in fact zero (null hypothesis).

## What is the interpretation of correlation coefficient?

The correlation coefficient describes how one variable moves in relation to another. A positive correlation indicates that the two move in the same direction, with a +1.0 correlation when they move in tandem. A negative correlation coefficient tells you that they instead move in opposite directions.

### How do you report correlation in research?

To report the results of a correlation, include the following:

1. the degrees of freedom in parentheses.
2. the r value (the correlation coefficient)
3. the p value.

How do you write correlation results in a thesis?

You report the results by saying something like: There has been a significant positive correlation between height and self-esteem after controlling for participants’ weight (r = . 39, p = . 034). You also need to make a table that will summarise your main results.