How Does the Beatles' Legacy Impact Radiohead's Chances of Greatness?

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SUMMARY

The discussion centers on the influence of The Beatles on Radiohead's perceived greatness, utilizing a probability transition matrix to analyze this relationship. According to music critics, 50% view The Beatles as great, 40% as moderate, and 10% as awful. The probability that Radiohead is great, given The Beatles' greatness, is calculated as 0.46. The user seeks clarification on calculating the probability of The Beatles being great given that Radiohead is considered great, using Bayes' theorem.

PREREQUISITES
  • Understanding of probability theory and Bayes' theorem
  • Familiarity with transition matrices in probability
  • Basic knowledge of music criticism and band influence
  • Ability to interpret statistical data and probabilities
NEXT STEPS
  • Study Bayes' theorem applications in real-world scenarios
  • Learn about probability transition matrices and their uses
  • Research the impact of influential bands on subsequent artists
  • Analyze music critic methodologies for evaluating band greatness
USEFUL FOR

Music analysts, statisticians, and anyone interested in the intersection of music influence and probability theory will benefit from this discussion.

Fusilli_Jerry89
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A band called Radiohead is inspired by an old band called The Beatles.
50% of music critics think the beatles was a great (G) band, 40% that it
was moderate (M) and 10% that it was awful (A). These critics have also
compiled the following table:0.8 0.1 0.1
0.1 0.9 0
0.2 0.3 0.5The table says that the probability of a new band (B2) being great given
that the inspiring band (B1) was great is P (B2 = GjB1 = G) = 0:8: Similarly, P (B2 = GjB1 = M) = 0:1, P (B2 = MjB1 = A) = 0:3, and so on.
Note that the numbers in the rows add up to 1, so the table is a probability
transition matrix.
1. Given what the critics think of the Beatles and the fact that the Beatles
inspired Radiohead, what is the probability that Radiohead is a great
band?
2. What is P (B1 = GjB2 = G)?

For 1 I get 0.50*0.8 + 0.40*0.1 + 0.10*0.2 = 0.46 which I think is correct.However, I am having trouble with part 2. I can write

P(B1 = G | B2 = G) = P(B2 = G | B1 = G)P(B1 = G) / P(B2 = G)

which leads to 0.8 * P(B1 = G) / P(B2 = G)

I also notice that P(B2 = G) = 1 cause we are told.

This leads to

P(B1 = G | B2 = G) = 0.8*P(B1 = G)
 
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Could P(B1 = G) be 0.5? (What the critics said)
 

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