One of the primary advantages of a repeated-measures design, compared to independent measures, is that it reduces the overall variability by removing variance caused by individual differences. The following data are from a research study comparing three treatment conditions:    Treatment 1  Treatment 2  Treatment 3     P  6                             9                     12         27  8                             8                       8         24  5                             7                       9         21  0                             4                       8         12  2                             3                       4           9  3                              5                      7         15    M = 4                 M = 6             M = 8    N = 18  T = 24                 T = 36             T = 48   G = 108  SS = 42              SS = 28           SS = 34  SX2 = 800   A) Assume that the data are from an independent-measures study using three separate samples, each with n = 6 participants. Ignore the column of P totals and use an independent-measures ANOVA with a = .05 to test the significance of the mean differences. B) Now assume that the data are from a repeated-measures study using the same sample of n = 6 participants in all three conditions. Use a repeated-measures ANOVA with a = .05 to test the significance of the mean differences. C) Explain why the two analyses lead to different conclusions.