What type of data is used in a Pearson's product-moment correlation?

Using Pearson's product-moment correlation involves assessing the linear relationship between two continuous variables. The correct choice, which identifies the appropriate type of data used in this correlation, is interval data.

Interval data is characterized by numerical values where the difference between values is meaningful, but there is no true zero point. This means that you can quantify how much one variable contributes to another and perform arithmetic operations necessary for calculating correlation coefficients.

While ratio data also allows for meaningful difference and has a true zero point, Pearson's correlation can be effectively applied to interval data, which is more common in psychological research when measuring constructs like intelligence scores or temperature.

Nominal data consists of categorical variables without any order, and ordinal data includes categories with a rank order but does not assume equal distances between ranks, making them unsuitable for Pearson's correlation. Hence, in the context of measuring relationships and applying statistical methods, interval and ratio data stand out as appropriate, with interval data being the focus for Pearson's correlation.