Correlation: Understanding Statistical Relationships

This set of flashcards covers key vocabulary and concepts related to correlation tests, including definitions, types of correlation, and important statistical principles.

Correlation

An inferential statistical test used to determine whether there is a significant relationship between two variables.

Pearson's r

A correlation coefficient that ranges from -1 to +1, indicating the strength and direction of a linear relationship between two variables.

Spearman's rho (p)

A non-parametric measure of rank correlation that assesses the strength and direction of association between two ranked variables.

Positive Correlation

A direct relationship where two variables move in the same direction; as one variable increases, the other also increases.

Negative Correlation

An inverse relationship where two variables move in opposite directions; as one variable increases, the other decreases.

Correlation Coefficient

A numerical measure that represents the strength and direction of a relationship between two variables.

Scatterplot

A graphical representation that displays values for typically two variables for a set of data, used to visualize the relationship between the variables.

Visualizing Correlational Data

The process of using scatterplots to explore the relationship between variables by examining the line of best fit and distribution of data points.

Assumptions of Correlation Tests

Conditions that must be met before running correlation tests, including linearity, normality of data, and absence of extreme outliers.

Causation vs. Correlation

The principle stating that correlation does not imply causation; significant relationships do not necessarily indicate one variable causing changes in another.