A business develops a multinomial logistic regression model to predict which of 3 customer groups customers belong to. The three customer groups are the Loyals, who faithful purchase from our company; the Switchers, who sometimes purchase from our company, and the Nevers, who never purchase from our company. The Nevers serve as the reference category in the model. The model makes its predictions from 3 variables: customer age, customer rating of our advertising, and customer price sensitivity. All 3 of these variables are quantitative. The output shows the following: mu1tinom(formu1a = grp ∼ age + advert + price, data = ecData) coefficients: (Intercept) lapsed loya7 ​ age 5.1110277−0.5934352​ advert −0.2849239−0.1610582​ price 0.84812031.1765146​−0.3118061−0.6419488​ You use the model to make predictions for a customer who is 38 years old, has a value on the advert variable of 8 and a value on the price variable of 4 and get the following: Using this information, what is the probability of this customer being Loyal? Being Lapsed? Being a Never? I am asking for absolute probability, not probability of being Loyal vs Never or Lapsed vs Never. Show your work.