Using the main model output (js.out) below, estimate the pro…

Using the main model output (js.out) below, estimate the probabilities that an Urban Private-sector worker responds ‘Low’, ‘Med’, or ‘High’. Model coefficients: (Intercept) Sector.L Region.L Med −0.103421 0.0672481 0.3158204 High −0.317653 −0.1203895 0.6421537 Coding: x₁ = 0 (Private), x₁ = 1 (Public); x₂ = 0 (Rural), x₂ = 1 (Urban). Compute π-hat_Low, π-hat_Med, and π-hat_High for a Private (x₁=0) Urban (x₂=1) worker.

The following log-likelihoods are from multinomial logistic…

The following log-likelihoods are from multinomial logistic regression models fit to a job satisfaction dataset (Response: High/Med/Low; predictors: Sector and Region): Minimal model (js.min.out): log Lik. = −1980.874 (df = 2) Main model (js.out): log Lik. = −1943.667 (df = 6) Saturated model(js.sat.out): log Lik. = −1940.553 (df = 8) Use the log-likelihood values to compute the deviance statistic to test: H₀: The minimal model is appropriate H_a: The main model (js.out) is better than the minimal model This deviance has 4 degrees of freedom. Carry out the test and state your conclusion.