Twenty-five patients with blisters were randomly assigned treatments. The treatments (Treatment) include Treatment A, Tr

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Twenty Five Patients With Blisters Were Randomly Assigned Treatments The Treatments Treatment Include Treatment A Tr 1 (193.49 KiB) Viewed 25 times

Twenty-five patients with blisters were randomly assigned treatments. The treatments (Treatment) include Treatment A, Treatment B, and Control. The number of days (num days) until the blisters heal is recorded. The distribution of days is assumed to be normal within treatment groups and variances are assumed to be equal. Use a = 0.01. aggregate(num.daxe. ~ Treatment, data=df, FUN = function(x) c(M=mean(x), SD=sd())) ## Treatment num days.M num_days. SD ## 1 A 7.250000 1.669046 ## 2 B 8.875000 1.457738 ## 3 C 10.111111 1.763834 fit <- agx(num daxs - Treatment, data=df) summary(fit) ## ## Treatment ## Residuals DE Sum Sq Mean Sq F value Pr(>F) 2 34.74 17.368 6.447 0.00626 ** 22 59.26 2.694 TukeyHSR(fit) $Treatment diff lur yrr p adj B-A 1.625000 -0.4365045 3.686505 0.1407700 C-A 2.861111 0.8576888 4.864533 0.0044884 C-B 1.236111 -0.7673112 3.239533 0.287957 e. What is the null and alternative hypothesis to test if the mean growth differs by treatment group? i. H:HA = MB = MC, HAMA # Mg Mc ii. H: MA E MBE MC,HAHA = MB = MC f. What is the result of testing this hypothesis? (a = 0.01) i. There is enough evidence to conclude that not all of the means are the same. ii. There is enough evidence to conclude that all of the means are different. iii. There is enough evidence to conclude that all of the means are the same. iv. There is NOT enough evidence to conclude that NOT all of the means are the same. g. Determine which means differ. (a = 0.01) i. There is not evidence that any of the means differ. ii. Hc< HA< MB iii. Mc = MA = MB iv. Mc differs from Ma, but not enough evidence to conclude that Mg differs from Mc and MA