Customers are used to evaluate a preliminary product design. In the past, 95% of highly successful products received good reviews, 60% of moderately successful products received good reviews, and 10% of poor products received good reviews. In addition, 40% of products have been highly successful, 35% of products have been moderately successful, and 25% of products have been poor ones.

a) What is the probability that a randomly selected product attains a good review?
b) If a new product attains a good review, what is the probability that the product is indeed a highly successful product?
c) If a new product does not attain a good review, what is the probability that the product is a moderately successful product?

a. 61.5%; b. About 61.8%; c. About 36.4%

Step-by-step explanation:

This is a kind of question that we can solve using the Bayes' Theorem. We have here all the different conditional probabilities we need to solve this problem.

According to that theorem, the probability of a selected product attains a good review is:

(1)

In words, the probability that a selected product attains a good review is an event that depends upon the sum of the conditional probabilities that the product comes from high successful product P(G|H) by the probability that this product is a highly successful product P(H), plus the same about the rest of the probabilities, that is, P(G|M)*P(M) or the probability that the product has a good review coming from a moderately successful product by the probability of being moderately successful, and a good review coming from a poor successful product by the probability of being poor successful or P(G|P)*P(P).

In this way, the probability that a randomly selected product attains a good review is the result of the formula (1). Where (from the question):

P(G|H) = 95% or 0.95 (probability of receiving a good review being a highly successful product)

P(G|M) = 60% or 0.60 (probability of receiving a good review being a moderately successful product)

P(G|P) = 10% or 0.10 (probability of receiving a good review being a poorly successful product)

P(H) = 40% or 0.40 (probability of  being a highly successful product).

P(M) = 35% or 0.35 (probability of  being a moderately successful product).

P(P) = 25% or 0.25 (probability of  being a poor successful product).

Then,

That is, the probability that a randomly selected product attains a good review is 61.5%.

We are looking here for P(H|G). We can express this probability mathematically as follows (another conditional probability):

We can notice that the probability represents a fraction from the probability P(G) already calculated. Then,

Then, the probability of a product that attains a good review is indeed a highly successful product is about 0.618 or 61.8%.

The probability that a product does not attain a good review is given by a similar formula than (1). However, this probability is the complement of P(G). Mathematically:

P(NG|H) = 1 - P(G|H) = 1 - 0.95 = 0.05

P(NG|M) = 1 - P(G|M) = 1 - 0.60 = 0.40

P(NG|P) = 1 - P(G|M) = 1 - 0.10 = 0.90

So

Which is equal to

P(NG) = 1 - P(G) = 1 - 0.615 = 0.385

Well, having all this information at hand:

Then, the probability that a new product does not attain a good review and it is a moderately successful product is about 0.364 or 36.4%.

no

explanation:

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