A measure of association, or relationship between two continuous variables, indicating how closely the data fits a straight line. There are two major limitations to correlation: (1) you can NOT infer causality, and (2) it measures only linear relationships.
Note: Correlation ≠ causation due to a likelihood of a spurious relationship (association without causation). This could be due to coincidence, directionality problem/reverse causality, and the third variable problem.
There must TWO CONTINUOUS variables
No IV, No DV. Just 2 variables: "Var1", "Var2"
Click "Regression"
Click "Correlation Matrix"
Enter Var1 and Var2 into the box on the right
Check "Person" under "Correlation Coefficients"
Check "Report significance" under "Additional Options"
Check "Flag significant correlations" under "Additional Options"
Person's r: Both a test statistic (direction) and measure of effect size (magnitude). (Note: In the social sciences, it is impossible to get a correlation as high as 1.0 due to human behavior. Instead, a magnitude closer to .4 is excellent!).
If r is closer to 0, there is a WEAK correlation magnitude.
If r is closer to 1, there is a STRONG correlation magnitude.
If r is positive, there is a POSITIVE correlation direction (both variables move together in the same direction).
If r is negative, there is a NEGATIVE correlation direction (the variables move in opposite directions).
p-value: The probability of detecting a meaningful relationship/difference when there is none. We are typically looking for a small value (p < 0.5).
If p < 0.5, reject the null hypothesis. There IS a difference.
If p > 0.5, accept the null hypothesis. There is NO difference.
df: Values in a study that have the freedom to vary and are essential for assessing the importance and validity of the null hypothesis.
Appropriate data visualization: Scatterplots
Sample table: https://apastyle.apa.org/style-grammar-guidelines/tables-figures/sample-tables#correlation
Sample write-up:
Hours of sleep per night and overall GPA were found to be moderately positively correlated, r(38)= .34, p=.032
Note: plugin the variables, magnitude, direction, df, Person's r, and p-value.
Visit https://www.guessthecorrelation.com/ to test your person's r prediction skills.
Visit https://www.tylervigen.com/spurious-correlations to laugh at some examples of spurious correlation.