1. The problem asks for the meaning of a "tie" in rank analysis in correlation. 2. In rank correlation methods like Spearman's rank correlation coefficient, data values are converted into ranks. 3. A "tie" occurs when two or more data points have the same value, so they share the same rank. 4. When ties happen, the average of the ranks that would have been assigned to these tied values is used for each tied value. 5. Handling ties properly is important because it affects the calculation of the correlation coefficient and ensures accurate measurement of association. 6. For example, if two values tie for ranks 3 and 4, each is assigned the average rank $\frac{3+4}{2} = 3.5$. 7. This adjustment prevents bias in the correlation calculation due to identical values. In summary, a "tie" in rank analysis means identical data values that share the same rank, and their ranks are averaged to maintain correct correlation calculations.