Sigma Percentile
JEE Main 2011
LEVELJEE Main

Animated Solution for Mathematics - Definite Integration: For , define . Then has

Select Answer:

Visualized Solution

Defining the Accumulator Function

  • Given function:
  • Interval:
  • Objective: Find points of local maxima and minima for

Applying the Leibniz Rule

  • To find extrema, we need the first derivative .
  • Using the Leibniz Rule:

Finding

  • Differentiating :
  • Result:

Finding Critical Points

  • Set to find critical points.
  • Since in the given interval, .

Solving

  • Equation:
  • Domain: or
  • Solutions:

Visualizing the Derivative

  • The graph of crosses the x-axis at and .
  • For , (Area is positive).
  • For , (Area is negative).

The Second Derivative Test Setup

  • To confirm maxima/minima algebraically, we use the Second Derivative Test.
  • First derivative:
  • Differentiating again using the Product Rule:

Calculating

Testing

  • Substitute into .
  • Since and :

Conclusion for

  • Since , the second derivative is negative.
  • Therefore, has a local maximum at .

Testing

  • Substitute into .
  • Since and :

Conclusion for

  • Since , the second derivative is positive.
  • Therefore, has a local minimum at .

Final Answer

  • Local maximum at
  • Local minimum at
  • Correct Option: 2

The Sigma Insight: Newton-Leibniz & Reduction Formulas

Solution Diagram

Analyzing the Setup

Welcome, future engineers! Today, we are going to unravel a problem that might look intimidating at first glance, but is actually a beautiful dance of calculus.
We are dealing with an accumulator function defined as:
Imagine this function as a machine that fills a bucket with water. As increases, the machine adds more water (area) to the bucket. Our goal is to find when the water level is at its highest (local maximum) and when it is at its lowest (local minimum) within the interval .

The Power of Leibniz

When you see an integral with a variable upper limit, your first instinct might be to try and solve the integral. Stop! Take a breath.
We don't need to find the closed-form expression for the integral. We only need to know how it changes. This is where the Leibniz Rule comes to our rescue.
It tells us that the derivative of an integral with a variable upper limit is simply the integrand evaluated at that limit. Applying this to our function, we get:

Finding the Critical Points

Now that we have the derivative, we are in the driver's seat. To find the peaks and valleys, we set .
This gives us the equation:
Since our domain is , we know is never zero. Thus, the only way for this product to be zero is if .
Within our specific interval , the solutions are:
These are our critical points, the moments where the 'filling' of our bucket changes direction.

The Second Derivative Test

While we could use the First Derivative Test, let's use the Second Derivative Test to be absolutely certain. We differentiate using the product rule:
Now, let's test our critical points. At :
Because , the function is concave down, confirming a local maximum at .
At :
Because , the function is concave up, confirming a local minimum at .

Conclusion

We have successfully navigated the problem! We found a local maximum at and a local minimum at .
Remember, calculus is not just about memorizing formulas; it is about understanding the behavior of functions. Keep exploring, keep questioning, and keep falling in love with the elegance of mathematics!

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