Final answer:
In MANOVA, significant functions can be identified using Roy-Bargman stepdown analysis or dimension reduction analysis; canonical correlation is not directly used for this purpose.
Step-by-step explanation:
In the context of Multivariate Analysis of Variance (MANOVA), to determine which function is significant, you can use a Roy-Bargman stepdown analysis or a dimension reduction analysis. Both of these analyses are used to assess the significance of canonical functions derived from the MANOVA. A Roy-Bargman stepdown analysis specifically tests the hypothesis that a particular canonical function explains a significant amount of additional variance after the variance explained by the preceding functions has been accounted for. On the other hand, dimension reduction analysis looks at the combined significance of all functions together from the first to any given function. Another related concept is a canonical correlation, which measures the relationship between two sets of variables; however, it is not directly used to determine which function within MANOVA is significant. Therefore, the correct answer would be using a Roy-Bargman stepdown analysis or a dimension reduction analysis, depending on the analysis goals.