10.21 These data are from the same source as those in Problem 10.3. We add data
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10.21 These data are from the same source as those in Problem 10.3. We add data for females to generate the two-way layout shown in Table 10.42. Table 10.42 Two-Way Layout for Problem 10.21 Antipyrine Clearance (Half-Life in Hours) Stage Stage IV Stage V Males 7.4 5.6 3.7 10.9 11.3 13.3 22 10.0 Females 9.6.3 7.1 11.0 8.3 4.3 6.6 6.0 1.3 9.4 7.9 (a) State an appropriate ANOVA model, null hypotheses, and alternative hypotheses State whether the model is fixed, random, or mixed. Define the population to which inferences are to be made. (b) Test the assumption of homogeneity of variance. (c) Test the assumption of normality using a probability plot (d Test the assumption of normality correlating residuals and rankits. (b) Graph the data. Is there any suggestion of interaction? Of main effects?Explanation / Answer
Statistical Method: We have two independent variables (Male and Female) and three groups (Stages). We can use two-way ANOVA to this data set. Two-way tells interaction between two independent groups on the dependent variable.
Null hypothesis: There is no difference between antipyrine clearance among different type of stages by gender distribution.
Alternative hypothesis: There is a significant difference between antipyrine clearance among different type of stages by gender distribution.
Two-way ANOVA the mode is fixed. The independent variable will be gender (male and female), so the inference based on gender distribution.
Homogeneity of variance: We can use Leven's test to test the homogeneity of variance, p-value = 0.3040. So we can not reject the null hypothesis that the variances are equal.
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