UPSC MainsMANAGEMENT-PAPER-II20162 Marks
Q1.

A and B decide to meet between 3 p.m. and 4 p.m., but each of them should wait no longer than 10 minutes for the other. Determine the probability that they meet.

How to Approach

This question is a probability problem disguised within a scenario. The approach involves visualizing the time interval (3 pm to 4 pm) as a continuous range and defining the 'success' condition as both A and B arriving within the 10-minute window of the other. We can solve this geometrically by representing the arrival times on a square and calculating the area representing successful meetings. The key is to understand the constraints imposed by the 10-minute waiting time for each person.

Model Answer

0 min read

Introduction

Probability, at its core, is the measure of the likelihood of an event occurring. In real-world scenarios, probabilistic reasoning is crucial for decision-making under uncertainty. This problem presents a classic example of geometric probability, where the probability of an event is determined by the ratio of areas. The scenario involves two individuals, A and B, attempting to meet within a specified time frame, each willing to wait for a limited duration. Understanding the constraints and visualizing the possible arrival times is essential to determine the probability of a successful meeting.

Understanding the Problem

Let's represent the time interval between 3 p.m. and 4 p.m. as 60 minutes. We can consider 'x' as the arrival time of A (in minutes after 3 p.m.) and 'y' as the arrival time of B (also in minutes after 3 p.m.). Both x and y lie between 0 and 60. The condition for them to meet is that |x - y| ≤ 10. This means A arrives within 10 minutes of B, or B arrives within 10 minutes of A.

Geometric Representation

We can visualize this problem graphically. Consider a square in the x-y plane where 0 ≤ x ≤ 60 and 0 ≤ y ≤ 60. The total area of this square represents all possible arrival time combinations for A and B, which is 60 * 60 = 3600 square minutes.

Defining the 'Success' Region

The condition |x - y| ≤ 10 can be rewritten as -10 ≤ x - y ≤ 10, which gives us two inequalities:

  • y ≥ x - 10
  • y ≤ x + 10
These inequalities define a strip within the square. The area of this strip represents the combinations of arrival times where A and B will meet.

Calculating the Area of the 'Success' Region

The area of the region where they *don't* meet consists of two right-angled triangles.

  • Triangle 1: y < x - 10. This triangle has vertices (10, 0), (60, 0), and (60, 50). Its area is (1/2) * 50 * 50 = 1250.
  • Triangle 2: y > x + 10. This triangle has vertices (0, 10), (0, 60), and (50, 60). Its area is (1/2) * 50 * 50 = 1250.
The total area where they don't meet is 1250 + 1250 = 2500. Therefore, the area where they *do* meet is 3600 - 2500 = 1100.

Calculating the Probability

The probability of A and B meeting is the ratio of the area of the 'success' region to the total area: Probability = (Area of 'success' region) / (Total area) = 1100 / 3600 = 11/36.

Alternative Approach - Considering Waiting Time

Another way to think about this is to consider the effective time window for each person. If A arrives at time 'x', B must arrive between x-10 and x+10. Similarly, if B arrives at time 'y', A must arrive between y-10 and y+10. The probability calculation remains the same, but this approach helps visualize the constraints.

Conclusion

Therefore, the probability that A and B meet, given their agreed-upon time frame and waiting limit, is 11/36. This problem demonstrates a practical application of geometric probability, where visualizing the problem space and calculating areas provides a clear solution. The key takeaway is understanding how constraints affect the possible outcomes and how to represent them mathematically.

Answer Length

This is a comprehensive model answer for learning purposes and may exceed the word limit. In the exam, always adhere to the prescribed word count.

Additional Resources

Key Definitions

Geometric Probability
Geometric probability is a branch of probability that deals with events occurring in a geometric space. It calculates probability by finding the ratio of areas, volumes, or lengths.
Conditional Probability
Conditional probability is the probability of an event occurring given that another event has already occurred. It is denoted as P(A|B), which reads as "the probability of A given B."

Key Statistics

According to a study by the University of California, Berkeley, the average wait time for a doctor's appointment is 18.5 days (as of 2023).

Source: University of California, Berkeley - Health Care Management Division

The average customer wait time in call centers has increased by 15% since the start of the COVID-19 pandemic (as of 2023).

Source: Contact Center IQ

Examples

Traffic Light Synchronization

Traffic light synchronization is a real-world application of probability and timing. Engineers calculate the optimal timing of lights to minimize wait times and maximize traffic flow, considering the probabilistic arrival of vehicles.

Frequently Asked Questions

What if A and B had different waiting times?

If A and B had different waiting times (e.g., A waits 10 minutes, B waits 5 minutes), the calculation would become more complex. The 'success' region would no longer be a simple strip, and the area calculation would require more careful consideration of the overlapping constraints.