Sigma Percentile
JEE Main 2006
LEVELJEE Main

Animated Solution for Mathematics - Differentiation: The function has a local minimum at

Select Answer:

Visualized Solution

Visualizing

  • Function:
  • Domain:
  • Goal: Find the x-coordinate of the local minimum.

The First Derivative Tool

  • To find critical points, we solve .
  • The derivative represents the slope of the tangent line.
  • At a local minimum or maximum, the tangent is horizontal.

Preparing for Differentiation

  • Rewrite using negative exponents.

Differentiating

  • Differentiating term by term:
  • Result:

Setting Derivative to Zero

  • Set to find critical points:

Solving for

  • Cross-multiply:
  • or
  • These are our critical points.

The Second Derivative Test

  • How do we know which point is the minimum?
  • If , the curve is concave up local minimum.
  • If , the curve is concave down local maximum.

Calculating

  • Start with
  • Differentiate again:

Testing

  • Substitute into :

Conclusion

  • Since , the curve is concave up.
  • Therefore, has a local minimum at .
  • Optional check: local maximum

The Sigma Insight: Maxima and Minima

Solution Diagram

Analyzing the Landscape

Welcome, future engineers! Today, we are going to explore the function .
Imagine you are standing on a landscape defined by this curve. As you move along the -axis, the function values rise and fall, creating a unique terrain.
Our mission is to find the lowest point, the local minimum, on this curve. This is not just about solving an equation; it is about understanding the geometry of change.

The Toolkit

Derivatives as Tangent Slopes
To find the 'valley' of our function, we need to know where the curve flattens out. In calculus, the first derivative tells us the slope of the tangent line at any point.
When the curve reaches a local minimum or maximum, the tangent line becomes perfectly horizontal, meaning its slope is zero.
To make our differentiation easier, we rewrite the function using negative exponents:
Now, applying the power rule term by term, we find the derivative:
This simplifies to:

The Search for Critical Points

Now, we set our derivative to zero to find the critical points:
By moving the negative term to the right, we get:
Cross-multiplying gives us . Here is where many students stumble!
When we take the square root of , we must consider both the positive and negative roots: and . These are our critical points, the locations where the curve is flat.

The Second Derivative Test

Concavity
We have two candidates, but which one is the valley? We use the second derivative test to check the concavity.
Differentiating again, we get:
The second derivative tells us about the 'smile' or 'frown' of the curve. If , the curve is concave up (a smile), indicating a local minimum. If , it is concave down (a frown), indicating a local maximum.
Testing , we find:
Since , the curve is concave up at , confirming it is a local minimum. Conversely, testing yields , confirming it is a local maximum.
Thus, the local minimum is at . Keep exploring, keep questioning, and let the math guide you!

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