The ice_cream data frame contains the result of a blind tasting of 90 ice creams, each of which is rated as poor, good, or excellent. It also contains the price of each ice cream classified into three categories. Consider the $R$ code below and its output.

(a) Write down the generalised linear model fitted by the code above.

(b) Prove that the fitted values resulting from the maximum likelihood estimator of the coefficients in this model are identical to those resulting from the maximum likelihood estimator when fitting a Multinomial model which assumes the number of ice creams at each price level is fixed.

(c) Using the output above, perform a goodness-of-fit test at the $1 \%$ level, specifying the null hypothesis, the test statistic, its asymptotic null distribution, any assumptions of the test and the decision from your test. (d) If we believe that better ice creams are more expensive, what could be a more powerful test against the model fitted above and why?