Hi @JudithS,
Welcome in the Community !
You'll find an answer about what is "Expected Value" here : Options for Ordinal Fits (jmp.com). It's a linear combination of the fitted probabilities of the class : Expected value = prob(1)x1 + prob(2)x2 + prob(3)x3 + ...
I have reproduced the calculation on an exemple dataset "Salt in Popcorn" with the formula for Expected Value in the column "Calculation Expected Value" :
:"Prob[1]"n * 1 + :"Prob[2]"n * 2 + :"Prob[3]"n * 3 + :"Prob[4]"n * 4 + :"Prob[5]"n * 5
I don't know if it's possible to have confidence intervals for the Y's, but you can save probability formulas for each class, as well as quantiles, and look for confidence intervals for the model's parameters.
I hope this first answer will help you,
Victor GUILLER
"It is not unusual for a well-designed experiment to analyze itself" (Box, Hunter and Hunter)