correlations

What is correlational research?

A type of research where variables are observed as they naturally occur without manipulation.

What does correlational research examine instead of causation?

Relationships or associations between variables.

Why is correlational research useful?

It allows researchers to examine relationships that cannot be ethically or practically manipulated.

What does it mean if two variables are correlated?

They change together in a systematic way.

Does correlation imply causation?

No, correlation does not demonstrate a cause-and-effect relationship.

What is the key difference between correlational and experimental designs?

Experimental designs manipulate variables to test causality, whereas correlational designs do not.

What is a correlational design?

A design where two or more variables are measured at the same time in a single group of participants.

How many variables are measured in a correlational design?

At least two variables.

Are variables manipulated in correlational designs?

No, variables are measured but not manipulated.

Give an example of data used in correlational research.

Self-report measures such as wellbeing or resilience.

What does it mean for variables to covary?

As one variable changes, the other increases, decreases, or stays the same.

What is covariance?

The degree to which two variables change together.

What is variance?

The average amount that data values differ from the mean.

How is covariance related to correlation?

Correlation standardises covariance to describe the strength and direction of a relationship.

What does a positive covariance indicate?

Both variables tend to increase or decrease together.

What does a negative covariance indicate?

As one variable increases, the other decreases.

What is the third variable problem?

The possibility that an unmeasured variable causes changes in both correlated variables.

Why does the third variable problem limit causal conclusions?

Because it is unclear which variable is responsible for the observed relationship.

What is a spurious correlation?

A correlation where no meaningful or direct relationship exists between variables.

What are common causes of spurious correlations?

Coincidence, third variables, multiple comparisons, or p-hacking.

Why are spurious correlations more common in large datasets?

Large datasets increase the likelihood of finding random patterns.

Why is correlational research often misreported in the media?

The media prefers simple cause-and-effect explanations.

Why is correlation particularly vulnerable to QRPs?

Many analytic choices can be made that inflate or misrepresent associations.

What is the correlation coefficient (r)?

A standardised statistic measuring the strength and direction of a relationship between two variables.

What does the direction of r indicate?

Whether the relationship is positive or negative.

What does the size of r indicate?

The strength of the relationship between variables.

What is the range of the correlation coefficient?

From -1 to +1.

What does r = +1 represent?

A perfect positive correlation.

What does r = -1 represent?

A perfect negative correlation.

What does r = 0 represent?

No linear relationship between variables.

How is r calculated conceptually?

By dividing covariance by the variability of each variable.

What r value is considered a small correlation?

Approximately ±0.1.

What r value is considered a medium correlation?

Approximately ±0.3.

What r value is considered a large correlation?

Approximately ±0.5.

Why are scatterplots useful in correlation analysis?

They visually display the relationship between two variables.

What information does a scatterplot show?

Direction, strength, and form of a relationship.

What does a positive scatterplot pattern indicate?

As one variable increases, the other also increases.

What does a negative scatterplot pattern indicate?

As one variable increases, the other decreases.

What is Pearson’s r?

A parametric correlation used to assess relationships between continuous variables.

What type of data is required for Pearson’s r?

Two continuous variables measured at interval or ratio level.

Is Pearson’s r suitable for ordinal data?

No, it is designed for continuous data.

What is Spearman’s rho?

A non-parametric correlation for ordinal or non-normally distributed continuous data.

What is Kendall’s tau?

A non-parametric correlation for ordinal or continuous data.

What is point-biserial correlation used for?

When one variable is continuous and the other is dichotomous.

What is a dichotomous variable?

A variable with two categories (e.g., yes/no, present/absent).

What are interval data?

Continuous data with equal intervals but no true zero.

What are ratio data?

Continuous data with equal intervals and a true zero.

What are nominal data?

Categorical data with no inherent order.

What are ordinal data?

Categorical data with a meaningful order.

Which JASP menu is used to run correlations?

Regression > Classical > Correlation.

What must be selected in JASP when running a correlation?

The variables and sample size.

How should a Pearson’s r result be reported?

By stating the direction, size, r value, degrees of freedom, and p value.

What does a statistically significant correlation indicate?

The observed relationship is unlikely to be due to chance.

What does r(8) mean in a correlation report?

The degrees of freedom, calculated as N − 2.

Why can a strong correlation still be misleading?

It does not establish causation and may be influenced by third variables.