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For each of the following functions of one variable, determine all local maxima and minima and indicate points of inflection (where /=0 ): a. f(x)=4x312x b. f(x)=4xx2 c. f(x)=x3

Short Answer

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Question: For the following functions, find the local maxima, local minima, and points of inflection: a. f(x)=4x312x b. f(x)=4xx2 c. f(x)=x3 Answer: a. Local maximum at x=1, local minimum at x=1, and no inflection points. b. Local maximum at x=2, no local minimum, and no inflection points. c. No local maxima or minima, and inflection point at x=0.

Step by step solution

01

a. f(x)=4x312x

First, we are going to find the first derivative of the function using the power rule: f(x)=34x31112x11=12x212 Now, let's set the first derivative equal to 0 to determine the critical points (i.e., where the local maxima and minima could occur): 12x212=0x2=1x=1,1 Next, we need to find the second derivative of the function to determine the concavity of the function: f(x)=212x21=24x Now, let's evaluate the second derivative at the critical points to determine if these points are indeed local maxima, local minima, or inflection points: - For x=1, we have f(1)=24. Since the second derivative is negative, this indicates a local maximum at x=1. - For x=1, we have f(1)=24. Since the second derivative is positive, this indicates a local minimum at x=1. Thus, there is a local maximum at x=1 and a local minimum at x=1. There are no inflection points as the second derivative is never equal to 0.
02

b. f(x)=4xx2

First, we need to find the first derivative of the function: f(x)=42x Now, let's set the first derivative equal to 0 to determine the critical points: 42x=0x=2 Next, we need to find the second derivative of the function to determine the concavity of the function: f(x)=2 Since the second derivative is negative, this indicates a local maximum at x=2. There are no inflection points, as the second derivative is always negative and never equals 0.
03

c. f(x)=x3

First, let's find the first derivative of the function: f(x)=3x2 Now, let's set the first derivative equal to 0 to determine the critical points: 3x2=0x=0 Next, we need to find the second derivative of the function to determine the concavity of the function: f(x)=6x Now, let's evaluate the second derivative at the critical point to determine if this point is a local maximum, local minimum, or inflection point: - For x=0, we have f(0)=0. Since the second derivative is equal to 0, there is an inflection point at x=0. Thus, there are no local maxima or minima, and there is an inflection point at x=0.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Local Maxima and Minima
Understanding local maxima and minima is a crucial part of microeconomic theory, which emphasizes decision-making and efficiency.

Let's consider a function that represents some economic quantity — for example, profit as a function of the quantity of goods produced. A local maximum of this function is a point where the profit is greater than at any nearby points, signifying the highest achievable profit in a local neighborhood around that point. Conversely, a local minimum is where the profit is less than at any adjacent point, indicating the lowest profits nearby.

Mathematically, a function's derivative provides information about its slope. At local maxima and minima, the slope is zero because the function levels off before changing direction. To find these points, one would calculate the first derivative of the function and set it equal to zero to find potential candidates, known as critical points.
Inflection Points
Moving to the concept of inflection points, these are crucial for economic models as they signify changes in the direction of curvature on a graph of a function. An inflection point occurs where a function shifts from concave upward (like a cup) to concave downward (like a cap), or vice versa.

An easy analogy to understand inflection points is a car driving over a hill; the hilltop would be a local maximum, and as the car drives down and the road begins to level out, the point where it stops being concave and starts becoming convex is an inflection point.

To determine inflection points mathematically, we investigate where the second derivative of the function changes sign. The second derivative gives information about the concavity of a function. If the second derivative is equal to zero and changes sign at that point, we have an inflection point. For the function given in the exercise, only function c, with the form f(x)=x^3, has an inflection point at x=0, because the second derivative at this point is zero, indicating a shift in concavity.
Second Derivative Test
The second derivative test is a practical tool for categorizing critical points as local maxima or minima. After identifying critical points by setting the first derivative of a function to zero, the second derivative test can determine the nature of these points.

According to the second derivative test, if the second derivative at a critical point is positive, the function is concave upward at that point, indicating a local minimum. If it's negative, the function is concave downward, and we have a local maximum. For example, from the solutions given, we can see function a, f(x)=4x^3-12x, assessed at critical points x=-1 and x=1. Here, the second derivative test tells us that x=-1 is a local maximum while x=1 is a local minimum.

However, when the second derivative is zero, the test is inconclusive, and we may resort to other methods to evaluate the critical point. This test helps in determining not only the nature of the extremities but also the general 'shape' of the graph around these points.

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Most popular questions from this chapter

Another function we will encounter often in this book is the "power function" \[ y=x^{5} \] where 051 (at times we will also examine this function for cases where 5 can be negative too, in which case we will use the form yx5/8 to ensure that the derivatives have the proper sign) a. Show that this function is concave (and therefore also, by the result of problem 2.8 , quasi-concave). Notice that the 8=1 is a special case and that the function is "strictly" concave only for 8<1 b. Show that the multivariate form of the power function is also concave (and quasi-concave). Explain why, in this case, the fact that/ 12=fi>i0 makes the determination of concavity especially simple. One way to incorporate "scale" effects into the function described in part b is to use the monotonic transformation \[ \left.g i_{x l,} x_{2}\right)=y i=\left[(x,)^{s}+\left(x_{2}\right)^{s}\right] y \] where y is a positive constant. Does this transformation preserve the concavity of the function? Is g quasi-concave?

The height of a ball t seconds after it is thrown straight up is 1Agt2+401 (where g is the acceleration due to gravity a. If g=32 (as on the earth), when does the ball reach a maximum height? What is that height? b. If g=5.5 (as on the moon), when does the ball reach a maximum height and what is that height? Can you explain the reasons for the difference between this answer and the answer for part (a)? c. In general, develop an expression for the change in maximum height for a unit change in g. Explain why this value depends implicitly on the value of g itself.

Suppose a firm's total revenues depend on the amount produced ( q ) according to the function \[ T R=70 q-q | \] Total costs also depend on q \[ T C=q^{2}+30 q+100 \] a. What level of output should the firm produce in order to maximize profits (77?TC)? What will profits be? b. Show that the second-order conditions for a maximum are satisfied at the output level found in part (a). c. Does the solution calculated here obey the "marginal revenue equals marginal cost" rule? Explain.

One of the most important functions we will encounter in this book is the Cobb-Douglas function: \[ y=(x \] where a and P are positive constants that are each less than one. a. Show that this function is quasi-concave using a "brute force" method by applying Equation 2.107 b. Show that the Cobb-Douglas function is quasi-concave by showing that the any contour line of the form y=c (where c is any positive constant) is convex and therefore that the set of points for which y>c is a convex set. c. Show that if a+y8>1 then the Cobb-Douglas function is not concave (thereby illus trating that not all quasi-concave functions are concave). (Note: The Cobb-Douglas function is discussed further in the Extensions to this chapter.)

Suppose that f(x,y)=xy. Find the maximum value for / if x and y are constrained to sum to 1. Solve this problem in two ways: by substitution and by using the Langrangian multiplier method.

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