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Group Activity In Exercises \(39-42,\) sketch a graph of a differentiable function \(y=f(x)\) that has the given properties. $$\begin{array}{l}{f^{\prime}(-1)=f^{\prime}(1)=0, \quad f^{\prime}(x)>0 \text { on }(-1,1)} \\ {f^{\prime}(x)<0 \text { for } x<-1, \quad f^{\prime}(x)>0 \text { for } x>1}\end{array}$$

Short Answer

Expert verified
The graph sketched would show three parts. The function \(f(x)\) decreasing for \(x<-1\), reaching a minimum at \(x=-1\), then increasing from \(x=-1\) to \(x=1\) to reach a maximum, and after \(x=1\), continue increasing for \(x>1\). The exact shape of the graph cannot be determined as no specific form of the function is given.

Step by step solution

01

Understand the function behavior based on derivative

Analyze the given conditions for \(f'(x)\) which is the derivative of the function. When \(f'(x)>0\), the function \(f(x)\) is increasing. When \(f'(x)<0\), the function \(f(x)\) is decreasing. We are given that \(f'(x)>0\) for \(x\) being in the intervals (-1,1) and \(x>1\), and \(f'(x)<0\) for \(x<-1\). This suggests that the function is increasing on the intervals (-1,1) and \(x>1\), and decreasing for \(x<-1\). At \(x=-1\) and \(x=1\), \(f'(x)=0\), thus these values are either local maximum or minimum.
02

Identify local extrema

Identify and label the maximum and the minimum points. This can be done by observing the function's behavior before and after these points. Since \(f'(x)\) shifts from negative to positive at \(x=-1\), this point is a local minimum. Since the value of \(f'(x)\) shifts from positive to negative at \(x=1\), this point is a local maximum.
03

Sketch the graph

Begin by plotting the points \((-1, f(-1))\) and \((1, f(1))\) which are local minimum and maximum respectively. Since details about \(f(x)\) are not given, these points can be plotted anywhere convenient on the \(y\)-axis as far as they reflect the relationship that \(f(-1)1\), the graph should be increasing. Draw it from the point \((1, f(1))\) sloping upwards.

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Most popular questions from this chapter

Group Activity Cardiac Output In the late 1860 s, Adolf Fick, a professor of physiology in the Faculty of Medicine in Wurtzberg, Germany, developed one of the methods we use today for measuring how much blood your heart pumps in a minute. Your cardiac output as you read this sentence is probably about 7 liters a minute. At rest it is likely to be a bit under 6 \(\mathrm{L} / \mathrm{min}\) . If you are a trained marathon runner running a marathon, your cardiac output can be as high as 30 \(\mathrm{L} / \mathrm{min.}\) Your cardiac output can be calculated with the formula $$$=\frac{Q}{D}$$ where \(Q\) is the number of milliliters of \(\mathrm{CO}_{2}\) you exhale in a minute and \(D\) is the difference between the \(\mathrm{CO}_{2}\) concentration \((\mathrm{mL} / \mathrm{L})\) in the blood pumped to the lungs and the \(\mathrm{CO}_{2}\) concentration in the blood returning from the lungs. With \(Q=233 \mathrm{mL} / \mathrm{min}\) and \(D=97-56=41 \mathrm{mL} / \mathrm{L}\) $$y=\frac{233 \mathrm{mL} / \mathrm{min}}{41 \mathrm{mL} / \mathrm{L}} \approx 5.68 \mathrm{L} / \mathrm{min}$$ fairly close to the 6 \(\mathrm{L} / \mathrm{min}\) that most people have at basal (resting) conditions. (Data courtesy of J. Kenneth Herd, M.D. Quillan College of Medicine, East Tennessee State University.) Suppose that when \(Q=233\) and \(D=41,\) we also know that \(D\) is decreasing at the rate of 2 units a minute but that \(Q\) remains unchanged. What is happening to the cardiac output?

Melting Ice A spherical iron ball is coated with a layer of ice of uniform thickness. If the ice melts at the rate of 8 \(\mathrm{mL} / \mathrm{min}\) , how fast is the outer surface area of ice decreasing when the outer diameter (ball plus ice) is 20 \(\mathrm{cm} ? \)

Writing to Learn You have been asked to determine whether the function \(f(x)=3+4 \cos x+\cos 2 x\) is ever negative. (a) Explain why you need to consider values of \(x\) only in the interval \([0,2 \pi] . \quad\) (b) Is f ever negative? Explain.

The Linearization is the Best Linear Approximation Suppose that \(y=f(x)\) is differentiable at \(x=a\) and that \(g(x)=m(x-a)+c(m\) and \(c\) constants). If the error \(E(x)=f(x)-g(x)\) were small enough near \(x=a,\) we might think of using \(g\) as a linear approximation of \(f\) instead of the linearization \(L(x)=f(a)+f^{\prime}(a)(x-a) .\) Show that if we impose on \(g\) the conditions i. \(E(a)=0\) ii. \(\lim _{x \rightarrow a} \frac{E(x)}{x-a}=0\) then \(g(x)=f(a)+f^{\prime}(a)(x-a) .\) Thus, the linearization gives the only linear approximation whose error is both zero at \(x=a\) and negligible in comparison with \((x-a)\) .

True or False If \(f^{\prime}(c)=0\) and \(f(c)\) is not a local maximum, then \(f(c)\) is a local minimum. Justify your answer.

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