Chapter 4: Problem 81
Let \(h\) and \(g\) have relative maxima at \(x_{0} .\) Prove or disprove: (a) \(h+g\) has a relative maximum at \(x_{0}\) (b) \(h-g\) has a relative maximum at \(x_{0}\).
Short Answer
Expert verified
(a) Proven; (b) Disproven.
Step by step solution
01
Understanding Relative Maxima
A function has a relative maximum at a point if the derivative at that point is zero (critical point) and the second derivative is negative. For function, say \(f(x)\), \(f'(x_0) = 0\) and \(f''(x_0) < 0\).
02
Given Conditions
Both \(h(x)\) and \(g(x)\) have a relative maximum at \(x_0\), which implies \(h'(x_0) = 0\), \(h''(x_0) < 0\) and \(g'(x_0)=0\), \(g''(x_0)<0\).
03
Proving (a): Evaluate \\(h+g\\) at \\(x_0\\)
Consider the sum \(f(x) = h(x) + g(x)\). The derivative \(f'(x) = h'(x) + g'(x)\). Evaluating this at \(x_0\), \(f'(x_0) = h'(x_0) + g'(x_0) = 0 + 0 = 0\). The second derivative is \(f''(x) = h''(x) + g''(x)\). Evaluating at \(x_0\), \(f''(x_0) = h''(x_0) + g''(x_0) < 0\) since both are negative. Hence, \(h+g\) has a relative maximum at \(x_0\).
04
Proving (b): Evaluate \\(h-g\\) at \\(x_0\\)
Consider the difference \(f(x) = h(x) - g(x)\). The derivative \(f'(x) = h'(x) - g'(x)\). Evaluating at \(x_0\), \(f'(x_0) = h'(x_0) - g'(x_0) = 0 - 0 = 0\). The second derivative is \(f''(x) = h''(x) - g''(x)\). Evaluating at \(x_0\), \(f''(x_0) = h''(x_0) - g''(x_0) = ext{negative} - ext{negative} = ext{unknown sign}\). This means we cannot conclude if \(h-g\) has a relative maximum at \(x_0\).
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Key Concepts
These are the key concepts you need to understand to accurately answer the question.
Derivatives
Derivatives are a fundamental concept in calculus. They measure how a function changes as its input changes.
Knowing how to work with derivatives gives a powerful tool for understanding the behaviour of functions in mathematical analysis.
- A derivative expresses the rate of change or slope of a function at any given point.
- If the derivative of a function, expressed as \(f'(x)\), equals zero at a specific point \(x_0\), this indicates that there might be a local extremum (a maximum or a minimum) at that point.
Knowing how to work with derivatives gives a powerful tool for understanding the behaviour of functions in mathematical analysis.
Critical Points
Critical points occur where the derivative of a function is zero or undefined. These points are key in determining where relative maxima or minima might occur.
- At critical points, the function's rate of change halts, potentially indicating a peak (maximum), a trough (minimum), or an inflection point.
- For example, if \(h(x)\) and \(g(x)\) reach a relative maximum at \(x_0\), both have their derivatives equal to zero there: \(h'(x_0) = 0\) and \(g'(x_0) = 0\).
Concavity
Concavity refers to the direction in which a curve bends. It is determined using the second derivative of a function:
- If the second derivative \(f''(x)\) is less than zero at a point, the function is concave down (like a hill) at that point, indicating a possible maximum.
- If \(f''(x)\) is greater than zero, the function is concave up (like a valley), pointing to a possible minimum.
- For \(h + g\) at \(x_0\), if both second derivatives \(h''(x_0)\) and \(g''(x_0)\) are negative, the combined function is concave down.
- However, for \(h - g\), each function's concavity may "cancel out," resulting in an uncertain sign for \(f''(x_0)\). This makes it impossible to declare it a maximum.