In Bayesian updating, if the prior favors p near 0.5 but data strongly supports p near 0.8, the posterior will likely:

In Bayesian updating, if the prior favors p near 0.5 but data strongly supports p near 0.8, the posterior will likely:

• A. Move toward 0.5
• B. Move toward 0.8 but not exactly
• C. Move away from 0.8
• D. Be exactly 0.5

Answer: (B)

Bayesian updating blends what you believed before with what the data say now. If the prior puts most probability around p = 0.5 but the data strongly favor p around 0.8, the posterior becomes a weighted compromise between those beliefs. It shifts away from 0.5 toward 0.8 because the data are informative, but it doesn’t snap exactly to 0.8 unless the data are overwhelmingly informative. So the posterior is likely to move toward 0.8, just not equal to it.

Bayesian updating blends what you believed before with what the data say now. If the prior puts most probability around p = 0.5 but the data strongly favor p around 0.8, the posterior becomes a weighted compromise between those beliefs. It shifts away from 0.5 toward 0.8 because the data are informative, but it doesn’t snap exactly to 0.8 unless the data are overwhelmingly informative. So the posterior is likely to move toward 0.8, just not equal to it.