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Chapter 19
Parameter Estimates
Figure
Parameter estimates
The parameter estimates show the effect of each predictor on Amount spent. The value of 518.249 for the intercept term indicates that the grocery chain can expect a shopper with a family who uses coupons from the newspaper and targeted mailings to spend $518.25, on average. You can tell that the intercept is associated with these factor levels because those are the factor levels whose parameters are redundant.
The shopfor coefficients suggest that among customers who use both mailed coupons and newspaper coupons, those without family tend to spend less than those with spouses, who in turn spend less than those with dependents at home. Since the tests of model effects showed that this term contributes to the model, these differences are not due to chance.
The usecoup coefficients suggest that spending among customers with dependents at home decreases with decreased coupon usage. There is a moderate amount of uncertainty in the estimates, but the confidence intervals do not include 0.
The interaction coefficients suggest that customers who do not use coupons or only clip from the newspaper and do not have dependents tend to spend more than you would otherwise expect. If any portion of an interaction parameter is redundant, the interaction parameter is redundant.
The deviation in the values of the design effects from 1 indicate that some of the standard errors computed for these parameter estimates are larger than those you would obtain if you assumed that these observations came from a simple random sample, while others are smaller. It is vitally important to incorporate the sampling design information in your analysis because you might otherwise infer, for example, that the usecoup=3 coefficient is not different from 0!
