Job Interview

Concise Answer (continued): Yes, use a sequence of flips to simulate a fair outcome.
Detailed Explanation (continued): For an unfair coin with any bias, you can flip it multiple times to create pairs of outcomes such as HT and TH. If the coin lands HT, you decide “heads,” and if it lands TH, you decide “tails.” If it lands HH or TT, you disregard the outcome and flip again. This method effectively ‘cancels out’ the bias, as HT and TH have the same probability, and you keep flipping until you get one of these combinations. This process ensures a 50% chance for each outcome and is known as the von Neumann extractor for fairness.
Now, let’s add more detail for parts b), c), and d) since these require a deeper explanation:

b) Expected Number of Flips (Detailed): The expected number of flips until the realization of an event is the inverse of the event’s probability. If the event is “getting heads” with P(H) = 1/3, the expected number of flips is 1/(1/3), which equals 3 flips. For two consecutive heads, we need to consider the geometric series formed by the probabilities of getting two heads in a row for each series of independent flips. The probability of getting two heads in a row is (1/3)^2 = 1/9, so the expected number of flips would be 1/(1/9) = 9 flips. However, because any flip sequence ending in “TH” resets the count for two consecutive heads, the calculation is a bit more complex, resulting in an expectation of 12 flips.

c) Reducing the Number of Flips (Concise): No strategy can change the expected number of flips because the coin’s bias is constant, and each flip is independent.

c) Reducing the Number of Flips (Detailed): Since the outcomes are determined by the biased probability of the coin, the expected number of flips for a given event cannot be changed without changing the underlying probability. However, what can be done is optimizing the process by avoiding unnecessary flips once the desired event has occurred or by using outcomes in combination to decide an event (as in the HT/TH method).

d) Strategy for Any Unfair Coin (Concise): The HT/TH method can be adapted for any bias.

d) Strategy for Any Unfair Coin (Detailed): The general approach to create a fair outcome from a biased coin is to flip the coin twice, creating four outcomes: HH, HT, TH, and TT. For any bias, the outcomes HT and TH will have the same probability, which allows us to use them to simulate a fair coin. If neither of these outcomes occurs, the flips are repeated. This strategy ensures a fair event from a biased coin with any probability distribution, as long as the coin is not deterministic (i.e., P(H) != 0 or 1).

Concise Answer: Divide and balance.
Detailed Explanation: Divide the balls into three groups of four. Use the scale to compare two groups. If they balance, the different ball is in the third group. If not, it’s in the heavier group. Then, from the identified group, place two balls on each side of the scale. If they balance, the remaining ball is the different one. If not, you’ve identified the heavier ball. You can determine which ball is different in the third weighing.

Simple Answer:

The probability that Alice and Bob meet is $\frac{7}{16}$.

Step-by-Step Answer:

1. Define the Problem: The meeting window is from 1:00 PM to 2:00 PM, which is 60 minutes. Both Alice and Bob arrive randomly within this window and wait for 15 minutes.

2. Consider the Time Range: The only way they fail to meet is if the time difference between their arrival times is more than 15 minutes.

3. Visualize on a 60×60 Square:

   • Imagine a square plot where one side represents Alice’s arrival time and the other represents Bob’s. The entire square represents all possible combinations of their arrival times within the hour.
   • The square has an area of $60\times 60=3600$ square units, where each unit represents a unique combination of arrival times (in minutes).

4. Calculate Non-meeting Zones:

   • The non-meeting zones are two triangles where the difference between their arrival times is greater than 15 minutes. Each triangle’s area represents the scenarios where they miss each other.
   • The area of each triangle is $\frac{1}{2}\times 45\times 45=1012.5$ square units. The total non-meeting area is $2\times 1012.5=2025$ square units.

5. Calculate Meeting Probability:

   • Subtract the non-meeting area from the total area to find the meeting area: $3600-2025=1575$ square units.
   • The probability of meeting is the ratio of the meeting area to the total area: $\frac{1575}{3600}=\frac{7}{16}$.

Therefore, the step-by-step calculation also shows that the probability of Alice and Bob meeting is $\frac{7}{16}$, confirming the simple answer provided earlier. This approach combines geometric visualization with basic probability principles to solve the problem.