Final answer:
The question involves conducting a Tukey HSD post-hoc test to determine which pairs of means are significantly different after an ANOVA test. The necessary calculations cannot be completed without specific data such as group means, group sizes, or mean square error. The Tukey HSD process includes computing a critical value and comparing it to differences between means to find significant differences.
Step-by-step explanation:
This question involves conducting a post-hoc test, specifically the Tukey's Honestly Significant Difference (HSD) test, after finding a significant F test in a one-way ANOVA. The goal of the post-hoc test is to compare all possible pairs of means to determine which ones are significantly different at an α level of 0.05. Given the provided data, we need more specific information such as the means of each group, the number of individuals in each group, the sum of squares within the groups, or the mean square error to calculate the Tukey HSD. Without these details, we cannot proceed to conduct the Tukey HSD for the pairs A-C, A-B, and B-C.
The general process of the Tukey HSD involves calculating the critical value from the Tukey distribution and multiplying it by the square root of the mean square error divided by the number of observations for each group. The resulting value is the minimum difference required for a pair of means to be considered significantly different. Comparisons are then made between the calculated differences of the means and the critical value. If the calculated difference between any two means is greater than the critical value, those means are considered significantly different.