Steady-state hemoglobin levels were measured on a total of N = 41 patients with k = 3 types of sickle cell disease. The k = 3 types are HB SS, HB ST (HB S/-thalassemia), and HB SC. The resulting data are displayed in Table 12.3.
SS | 7.2 | 7.7 | 8.0 | 8.1 | 8.3 | 8.4 | 8.4 | 8.5 | 8.6 | 8.7 | 9.1 | 9.1 | 9.1 | 9.8 | 10.1 | 10.3 |
ST | 8.1 | 9.2 | 10.0 | 10.4 | 10.6 | 10.9 | 11.1 | 11.9 | 12.0 | 12.1 | 3 | |||||
SC | 10.7 | 11.3 | 11.5 | 11.6 | 11.7 | 11.8 | 12.0 | 12.1 | 12.3 | 12.6 | 12.6 | 13.3 | 13.3 | 13.8 |
13.9 |
a. Use side-by-side boxplots and normal probability plots to investigate the ANOVA assumptions of normality and homoscedasticity. Do these assumptions seem plausible? Why or why not? b. Use ANOVA to test the null hypothesis that the three types of sickle cell disease have the same mean hemoglobin levels. Use a significance level of ? = 0.05 and organize your calculations in an ANOVA table.
Note: For this problem, please calculate/compute all information (such as Sum of Squares, Mean Squares, Test Statistic and P-value) you need for the ANOVA table before checking with the “ANOVA” function in R. Please include appropriate labels in your plots!
not homo scedastic
for sc....normslity assumption holds
plot for st
normality assumption does not hold as the points are not on st line y=x
plot for st..nonotmalityholnonotmalityholds
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