My apologies if this is a basic question because I am no mathematician. Struck on my work on this, so came here to get some help.
I am working on this bayesian estimate explained here.
This is a bayesian estimator used to find out the Top 250 list of all the movies in Imdb.com with the following factors.
W= weighted rating
R= average for the movie as a number from 0 to 10 (mean) = (Rating)
v= number of votes for the movie = (votes)
m= minimum votes required to be listed in the Top 250 (currently 25000)
C= the mean vote across the whole report (currently 7.1)
Here what I am trying to do is to find the required number of votes and rating for a normal movies to get into the Top 250 list.
This is how I do it:
- Find the Weighted Rating(W) of 250th movie in the list.
- subtract 0.0001 to the W to get newW.
- With the new weighted rating I have to calculate the required number of votes and the rating.
This 3rd step is where I got struck.
Can you simplify me an expression to calculate
1. required number of votes
2. Average Rating
Also the new required number votes should exclude the existing votes.