Scientists have developed a way to measure causality between two signals in noisy data, like in Economics and Neuroscience. Granger causality shows if one signal's past can predict the future of another signal better than its own past can. This can happen even without direct interaction between the signals. The researchers explain how to calculate Granger causality in both time and frequency domains, using examples in the frequency domain. They also mention other methods to measure causality and discuss the limitations and applications of Granger causality.