# Exercise 3 The following chunk performs an analysis of variance (ANOVA) test of independence between the multilevel categorical variable 'strain' and the numerical variable 'log.viral.load'. This test works by asking whether the whole-sample or between-strain variance is significantly greater than the within-strain variance. It helps us to avoid the guggggtigglly increasing multiple-testing problem that arises when we analyze multilevel categorical variables such as strain, if the other variable is numerical. I4 \"'{r} anovaClmeormula = log.viral.load ~ strain, data = fishDat)) \\\\\\ >> Analysis of Variance Table Response: log.viral.load DF Sum Sq Mean Sq F value Pr(>F) strain 2 4.856 2.4279 2.0937 0.1268 Residuals 152 176.261 1.1596 The P-value For this test of independence is 0.1268. *Given what you know about tests of independence and what you know about Pvalues, what should you conclude about the null hypothesis (one sentence)? What does this lead you to conclude about the association between the strain variable and the log viral load variable (one sentence)?* ***