Sigma Percentile
JEE Main 2003
LEVELJEE Main

Animated Solution for Mathematics - Differentiation: If the function , where , attains its maximum and minimum at and respectively such that , then equals

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Visualized Solution

Understanding the Function

  • Given function:
  • Constraint:
  • Local maximum at , local minimum at
  • Given condition:

Finding the First Derivative

  • To find the critical points, we need the first derivative .

Differentiating

Setting

  • For critical points, set :
  • Divide the entire equation by :

Solving for Critical Points

  • Factorizing the quadratic equation:
  • Critical points: and

The Second Derivative Test

  • To determine maxima and minima, we use the second derivative .

Testing for Maxima

  • Substitute into :
  • Since ,
  • Local Maximum at , so

Testing for Minima

  • Substitute into :
  • Since ,
  • Local Minimum at , so

Applying the Condition

  • We found and .
  • Given condition:
  • Substituting the values:

Solving for

  • Rearranging the equation:
  • Possible values: or

Final Conclusion for

  • Constraint check: The problem states .
  • Therefore, is rejected.
  • The only valid solution is .

The Sigma Insight: Maxima and Minima

Solution Diagram

Analyzing the Cubic Landscape

Welcome, future engineer. Today, we are not just solving an algebra problem; we are exploring the topography of a cubic function. Imagine you are standing on a landscape defined by the function .
This is a classic cubic curve that rises, falls, and rises again. Our mission is to find the specific value of the parameter that dictates the shape of this landscape, given that the peak (local maximum) occurs at and the valley (local minimum) occurs at , with the elegant constraint .

The Calculus of Slopes

To understand where the peaks and valleys of our landscape lie, we must look at the slope. In calculus, the slope of the tangent line at any point is given by the first derivative, . We want to find the points where the landscape is perfectly flat—the critical points.
Let us differentiate our function:
Applying the power rule term by term, we obtain:
This quadratic expression is the key to our mystery. By setting , we find the exact locations where the slope is zero.

Unlocking the Critical Points

Setting the derivative to zero gives us:
To make this manageable, we divide the entire equation by :
Now, we factorize. We are looking for two numbers that multiply to and add to . Those numbers are and . Thus, the equation becomes:
This reveals our two critical points: and . We must now determine which is the peak and which is the valley.

The Second Derivative Test

To distinguish between the maximum and the minimum, we invoke the Second Derivative Test. We differentiate one more time:
Now, let us test our points. For :
Since the problem states , is negative. A negative second derivative indicates concavity downwards, which means we have found our local maximum. Thus, .
For :
Since , is positive. A positive second derivative indicates concavity upwards, which means we have found our local minimum. Thus, .

The Final Synthesis

We have our variables: and . The problem provides the final piece of the puzzle: . Substituting our values, we get:
Rearranging this, we have , which factors to . This gives us two potential solutions: or .
However, we must respect the constraint . Therefore, we reject and accept as our definitive answer.

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