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Published 20 hours ago • verified publisher icon CamDavidsonPilon

A/B Testing Joint Explanation

Open bluesky314 opened this issue 5 years ago • 1 comments

The double_joint_log_prob in ch2 A/B testing is not explained at all. Why do we return ( rv_prob_A.log_prob(prob_A) + rv_prob_B.log_prob(prob_B) + tf.reduce_sum(rv_obs_A.log_prob(observations_A)) + tf.reduce_sum(rv_obs_B.log_prob(observations_B)) )

would'nt this corrospond to finding the posterior that observations_A AND observations_B occur and not the difference? Can some one provide a derivation?

bluesky314 avatar Apr 21 '19 07:04 bluesky314

Do we find the joint of prob_A,prob_B and then marginalising over to get the individual posteriors? Why not do it separately then?

Why does 'burnin' stand for in burned_prob_A_trace_ = posterior_prob_A_[burnin:] ?

bluesky314 avatar Apr 21 '19 09:04 bluesky314