MTB > # Chapter 2 - proportion inference with discrete priors
MTB > # Example:  let p be the batting average of a 
MTB > # ballplayer -- either p=.2,.28 or .36 with probs
MTB > # .4, .5, .1, respectively.  Player gets 6 hits in 20 at-bats.
MTB > # What have you learned about p?

MTB > name c1 'p' c2 'prior'
MTB > set c1
DATA> .2 .28 .36
DATA> set c2
DATA> .4 .5 .1
DATA> end
MTB > prin c1-c2

 Row      p  prior

   1   0.20    0.4
   2   0.28    0.5
   3   0.36    0.1

MTB > exec 'p_disc'
 
INPUT OBSERVED NUMBER OF SUCCESSES AND FAILURES:
DATA> 6 14

 Row      p  prior  P_x_PRIO      LIKE  PRODUCT       POST   P_x_POST

   1   0.20    0.4     0.080    580546   232218   0.283518   0.056704
   2   0.28    0.5     0.140   1000000   500000   0.610455   0.170927
   3   0.36    0.1     0.036    868424    86842   0.106027   0.038170
   4                   0.256                                 0.265801