Given the provided F-statistics and p-values, let's analyze the results in the context of the significance level $\alpha = 0.05$:

1. For Treatments:

   • F-statistic = 2.14, p-value = 0.095
   • Since $p = 0.095 > \alpha = 0.05$, we fail to reject the null hypothesis for treatments. This means there is no significant difference in treatment means.

2. For Blocks:

   • F-statistic = 3.56, p-value = 0.018
   • Since $p = 0.018 < \alpha = 0.05$, we reject the null hypothesis for blocks. This means there is a significant difference in block means.

Conclusion:

There is a significant difference in block means, but no significant difference in treatment means.

Thus, the correct answer is:

There is a significant difference in block means, but not in the treatment means.

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Do you want further details or have any questions?

Here are 5 related questions to expand on this topic:

1. What is the null hypothesis in a two-way ANOVA for treatments and blocks?
2. How do you calculate the F-statistic in a two-way ANOVA?
3. Why is the p-value compared to the significance level $\alpha$?
4. What would a significant interaction effect mean in a two-way ANOVA?
5. How does the assumption of homogeneity of variances affect the results of a two-way ANOVA?

Tip: In ANOVA, always check if the interaction between factors (if present) is significant before interpreting main effects like treatments or blocks.