Given data:
| Plant A | Plant B | |
|---|---|---|
| Manufactured | \(60\%\) | $40\%$ |
| Standard quality | $80\%$ | $90\%$ |
Define:
The probabilities are:
\( P(C) = \frac{60}{100}, \quad P(B) = \frac{40}{100}. \)
The conditional probabilities are:
\( P(A \mid C) = \frac{80}{100}, \quad P(A \mid B) = \frac{90}{100}. \)
Using Bayes’ theorem:
\[ P(B \mid A) = \frac{P(A \mid B) P(B)}{P(A \mid B) P(B) + P(A \mid C) P(C)}. \]
Substitute the values:
\[ P(B \mid A) = \frac{\frac{90}{100} \times \frac{40}{100}}{\frac{90}{100} \times \frac{40}{100} + \frac{80}{100} \times \frac{60}{100}}. \]
Simplify:
\[ P(B \mid A) = \frac{90 \times 40}{90 \times 40 + 80 \times 60} = \frac{3600}{3600 + 4800} = \frac{3600}{8400} = \frac{3}{7}. \]
Now:
\[ 126p = 126 \times \frac{3}{7} = 54. \]
Final Answer: \( 126p = 54. \)
To solve this problem, we'll use Bayes' Theorem, which helps in finding the probability of an event based on prior knowledge of conditions related to the event. Let's define the events as follows:
We need to find the probability \(P(A_2 | B)\), the probability that a motorcycle was manufactured at Plant B given that it is of standard quality.
The given probabilities are:
Using Bayes' theorem:
\(P(A_2 | B) = \frac{P(B | A_2) \cdot P(A_2)}{P(B)}\)
To find \(P(B)\), we use the law of total probability:
\(P(B) = P(B | A_1) \cdot P(A_1) + P(B | A_2) \cdot P(A_2)\)
Plugging in the values:
\(P(B) = 0.8 \cdot 0.6 + 0.9 \cdot 0.4 = 0.48 + 0.36 = 0.84\)
Now we can calculate \(P(A_2 | B)\):
\(P(A_2 | B) = \frac{0.9 \cdot 0.4}{0.84} = \frac{0.36}{0.84}\)
Simplifying the fraction:
\(P(A_2 | B) = \frac{9}{21} = \frac{3}{7}\)
According to the problem, we need to find \(126p\), where \(p = P(A_2 | B)\):
\(126p = 126 \cdot \frac{3}{7} = 54\)
Therefore, the correct answer is 54.
A conducting bar moves on two conducting rails as shown in the figure. A constant magnetic field \( B \) exists into the page. The bar starts to move from the vertex at time \( t = 0 \) with a constant velocity. If the induced EMF is \( E \propto t^n \), then the value of \( n \) is _____. 