Please answer this with a brief explanation, use R if necessary, thanks!

Below, you will find an ANOVA table reporting the results of a (hypothetical) experiment on the effects of using different Instagram filters on a measure of social media engagement. A randomized complete block design is used; the identity of the influencers making the posts are used as a blocking variable. Assume that an additive two-way fixed-effect ANOVA model is appropriate here. (a) Does influencer identity make sense as a blocking variable? Explain. (b) At a = 0.01, can you conclude that different filters have different levels of engagement? Explain. (c) Would you say that this design is more efficient than a complete randomized design? Explain, being as specific as possible. Df Sum Sq Mean Sq F value Pr(>F) influencer 3 1.98 0.66 73.45 0.0026 filter 1 0.04 0.04 4.71 0.1184 Residuals 0.03 0.01