Bayes Theorem
P(B/A)=P(A and B)/P(A) but from Bayes Theorem we have
P(B/A) = P(A/B)*P(B)/P(A)
P(B/A) = P(A/B)*P(B)/P(A)
in our problem let A = identify correctly and B = cat person
therefore A' = identify incorrectly and B' = dog person
therefore A' = identify incorrectly and B' = dog person
P(A) = P(A/B)*P(B) + P(A/B')P(B')
Note the tree diagram in the written work.
The values used and obtained are as follows
P(B) = .33
P(B') = .67
P(A/B) = .96
P(A'/B) = .04
P(A/B') = .71
P(A'/B') = .29
P(A and B) = .33(.76) = .3168
P(A' and B) = .33(.04) = .0132
P(A and B') = .67(.71) = .4757
P(A' and B') = .67(.29) = .1943
P(B') = .67
P(A/B) = .96
P(A'/B) = .04
P(A/B') = .71
P(A'/B') = .29
P(A and B) = .33(.76) = .3168
P(A' and B) = .33(.04) = .0132
P(A and B') = .67(.71) = .4757
P(A' and B') = .67(.29) = .1943
Notice that all the joint probabilities add to 1
Now put those values into the formula and you'll get P(B/A) = .3997