As an example, suppose we would like to model the data on cholesterol
levels in rural and urban Guatemalans, examined in Section
, as a one way ANOVA model. The boxplots we
obtained in Section
showed that the samples
were skewed and the center and spread of the urban sample were larger
than the center and spread of the rural sample. To compensate for
these facts I will use a normal ANOVA model for the logarithms of the
data:
> (def cholesterol (oneway-model (list (log urban) (log rural)))) Least Squares Estimates: Group 0: 5.377172 (0.03624821) Group 1: 5.099592 (0.03456131) R Squared: 0.4343646 Sigma hat: 0.1621069 Number of cases: 42 Degrees of freedom: 40 Group Mean Square: 0.8071994 (1) Error MeanSquare: 0.02627865 (40) CHOLESTEROL >
The function "2D oneway-model requires one argument, a list of the lists or vectors representing the samples for the different groups. The model "2D cholesterol can respond to all regression messages as well as a few new ones. The new ones are
:BOXPLOTS :ERROR-MEAN-SQUARE :ERROR-DF :GROUP-MEAN-SQUARE :GROUP-DF :GROUPED-DATA :STANDARD-DEVIATIONS