Chapter 14: Problem 77
A function \(f\) is such that \(f^{\prime}(4)=f^{\prime \prime}(4)=0\) and \(f\) has minimum value 10 at \(x=4\). Then \(f(x)=\) (A) \(4+(x-4)^{4}\) (B) \(10+(x-4)^{4}\) (C) \((x-4)^{4}\) (D) None of these
Short Answer
Expert verified
(B) \(10 + (x - 4)^4\)
Step by step solution
01
Understanding the condition of derivatives
We are given that \(f^{\prime}(4) = f^{\prime \prime}(4) = 0\). This means that at \(x = 4\), the first and second derivatives of the function are both zero. To have a local minimum at this point, usually, the second derivative should be positive, but since it is zero, we need to analyze further or find a higher derivative.
02
Analyze possible functions
The function that checks the properties \(f^{\prime}(4) = 0\) and \(f^{\prime \prime}(4) = 0\), while having a minimum at \(x = 4\), could be of the form \(f(x) = a(x-4)^n + c\), where \(n > 2\) and we desire \(f(4) = 10\). For \(n = 4\), the third and fourth derivatives are needed to decide the concavity.
03
Substituting specific forms into conditions
Suppose \(f(x) = (x-4)^4 + c\). Then \(f(4) = 0^4 + c = c\). Given the minimum value is 10 at \(x = 4\), we must have \(f(4) = 10\). Thus, \(c = 10\), showing an expression \(f(x) = (x-4)^4 + 10\).
04
Verifying specific functional form
Given \(f(x) = 10 + (x-4)^4\), verify \(f^{\prime}(4) = 0\) and \(f^{\prime \prime}(4) = 0\). The derivative, \(f^{\prime}(x) = 4(x-4)^3\) and \(f^{\prime \prime}(x) = 12(x-4)^2\), both evaluate to 0 at \(x = 4\), satisfying the conditions.
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Key Concepts
These are the key concepts you need to understand to accurately answer the question.
Optimization
Optimization is the process of finding the best possible solution or outcome in a given situation. In mathematics, specifically calculus, it often involves finding the maximum or minimum values of a function. This process relies heavily on understanding the nature of the function and its derivatives.
- By setting the first derivative equal to zero, we identify critical points, which indicate where potential maxima or minima might occur.
- The second derivative can tell us more about the concavity of these points, helping determine if they are maxima, minima, or points of inflection.
Derivatives
Derivatives are a fundamental concept in calculus that measure how a function changes as its input changes. The first derivative of a function gives the slope of the tangent line at any point, telling us whether the function is increasing or decreasing at that point.
- If the first derivative is zero, the function has a horizontal tangent at that point, suggesting a potential maximum, minimum, or saddle point.
- The second derivative provides information on the concavity of the function. A positive second derivative indicates concavity upwards, suggesting a local minimum, while a negative one indicates concavity downwards, suggesting a local maximum.
Local Minimum
A local minimum of a function is a point where the function value is lower than at any nearby points. At a local minimum, the function changes direction from decreasing to increasing. For a student understanding this concept, it is essential to remember:
- The first derivative is zero at a local minimum, indicating a potential change in direction.
- In typical scenarios, the second derivative being positive confirms the presence of a local minimum.