Sigma Percentile
JEE Main 2020 (5 September Shift 1)
LEVELJEE Main

Animated Solution for Mathematics - Sets and Relations: A survey shows that of the persons working in an office like coffee, whereas like tea. If denotes the percentage of them, who like both coffee and tea, then cannot be :

Select Answer:

Visualized Solution

Visualizing the Universal Set

  • Let the total population be the universal set.

Defining the Sets

  • Let be the set of people who like coffee.
  • Let be the set of people who like tea.

The Intersection

  • Let be the percentage of people who like both.

Principle of Inclusion-Exclusion

  • Using the formula for the union of two sets:

Substituting the Values

  • Substitute the known percentages into the formula:

Simplifying the Expression

  • Add the constant values:

Constraint 1: Upper Bound of Union

  • The union cannot exceed the total population.

Solving for the Lower Bound

  • Substitute the simplified expression:

Constraint 2: Upper Bound of Intersection

  • The intersection cannot exceed the size of the smallest individual set.

Solving for the Upper Bound

  • Substitute the set sizes:

Combining the Bounds

  • Combine the lower and upper bounds to find the valid range for :

Evaluating the Options

  • Given options:
  • We need to find the value that does NOT satisfy .

Final Conclusion

  • is strictly less than .
  • Therefore, cannot be .

The Sigma Insight: Types of Sets and Set Operations

Solution Diagram

Analyzing the Setup

Welcome, fellow traveler of the mathematical arts. Today, we are not just solving a problem about coffee and tea; we are exploring the boundaries of possibility.
Imagine you are standing in the middle of a bustling office. You have a clipboard, and you are conducting a survey. You find that of your colleagues are coffee enthusiasts, and are tea lovers.
At first glance, this seems straightforward. But as we dive deeper, we encounter a beautiful, logical puzzle: how many people like both? And more importantly, what are the limits of this overlap?

The Universal Boundary

Before we touch a single variable, we must establish our stage. In any survey involving percentages, the entire population is our universal set, which we define as .
This is our absolute ceiling. No matter how you slice the data, the percentage of people who like at least one beverage—the union of our sets—cannot exceed this boundary. This is the first law of our reality in this problem.

The Master Key of Inclusion-Exclusion

Now, let us define our players. Let be the set of coffee lovers, where , and be the set of tea lovers, where .
We are looking for , the percentage of people who like both, which is mathematically represented as the intersection, . To connect these, we invoke the Principle of Inclusion-Exclusion:
This formula is the heartbeat of set theory. It tells us that if we simply add the coffee lovers and the tea lovers, we are double-counting the people who like both. By subtracting , we correct this double-counting and find the true union.

The Two Walls of Constraint

Substituting our values, we get , which simplifies to:
Now, we hit the exciting part: the constraints. We have two 'walls' that define the range of .
The first wall is the total population. Since , we substitute our expression:
Rearranging this, we find . This is our lower bound. It tells us that at least of the office must like both, or else the total percentage of people who like at least one drink would exceed .
But there is a second wall. The intersection cannot be larger than the individual sets themselves. Specifically, it cannot exceed the smaller of the two sets.
Since and , the intersection must satisfy , which means . This is our upper bound.

The Final Verdict

We have arrived at our destination. The valid range for is the interval . Any value outside this range is a logical impossibility.
Looking at our options, we see , , , and . We are looking for the value that cannot be.
Since is strictly less than , it falls outside our valid range. It is the impossible value. By understanding the constraints of the system, we have not just solved for ; we have mapped the entire landscape of possibility.

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