MATH 112: Optimization Review for Exam II - Prof. Jennifer Taggart, Study notes of Mathematics

A review for exam ii of math 112, focusing on optimization. It covers derivative rules, functions of one variable, and functions of two variables. Topics include finding local and global optima, using the second derivative test, and computing partial derivatives. Additionally, it discusses maximizing tr(q) and optimizing the slope of a diagonal line, as well as finding the best-fitting line for a set of data.

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Uploaded on 03/10/2009

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MATH 112
REVIEW FOR EXAM II
OPTIMIZATION
I. Derivative Rules
There will be a page of derivatives on the exam. Know how to apply all the
derivative rules. (WS 12 and 13)
II. Functions of One Variable
Be able to distinguish between local and global optima.
Be able to find the global maximum and minimum of a function y=f(x) on
the interval from x=ato x=b, using the fact that optima may only occur
where f(x) has a horizontal tangent line and at the endpoints of the interval.
Step 1: Compute f0(x).
Step 2: Find all values of xat which f0(x) = 0.
Step 3: Plug all the values of xfrom Step 2 that are in the interval from ato
band the endpoints of the interval into the function f(x).
Step 4: Sketch a rough graph of f(x) and pick off the global max and min.
Be familiar with the following two applications:
Maximizing T R(q) starting with a demand curve. (WS 15)
Optimizing the slope of a diagonal line through a given curve. (WS 16)
Understand how to use the Second Derivative Test. (WS 17)
If f0(a) = 0 and:
f00(a)>0, then f(x) has a local min at x=a.
f00(a)<0, then f(x) has a local max at x=a.
f00(a) = 0, then the test tells you nothing.
IMPORTANT!!! For the Second Derivative Test to work, you must have
f0(a) = 0. If f00 (a)>0 but f0(a)6= 0, then the graph of f(x) is concave up at
x=abut f(x) does not have a local min there.
III. Functions of Two Variables
Be able to compute overall, incremental, and instantaneous rates of change of a
function of two variables. (WS 18A)
Be able to compute partial derivatives using all the derivative rules.
Know how to find the candidates for maxima and minima in a function of two
variables. (Take both partial derivatives, set them equal to 0, and solve the
resulting system of equations.)
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MATH 112

REVIEW FOR EXAM II

OPTIMIZATION

I. Derivative Rules

  • There will be a page of derivatives on the exam. Know how to apply all the derivative rules. (WS 12 and 13)

II. Functions of One Variable

  • Be able to distinguish between local and global optima.
  • Be able to find the global maximum and minimum of a function y = f (x) on the interval from x = a to x = b, using the fact that optima may only occur where f (x) has a horizontal tangent line and at the endpoints of the interval. Step 1: Compute f ′(x). Step 2: Find all values of x at which f ′(x) = 0. Step 3: Plug all the values of x from Step 2 that are in the interval from a to b and the endpoints of the interval into the function f (x). Step 4: Sketch a rough graph of f (x) and pick off the global max and min.
  • Be familiar with the following two applications:
    • Maximizing T R(q) starting with a demand curve. (WS 15)
    • Optimizing the slope of a diagonal line through a given curve. (WS 16)
  • Understand how to use the Second Derivative Test. (WS 17) If f ′(a) = 0 and: - f ′′(a) > 0, then f (x) has a local min at x = a. - f ′′(a) < 0, then f (x) has a local max at x = a. - f ′′(a) = 0, then the test tells you nothing. IMPORTANT!!! For the Second Derivative Test to work, you must have f ′(a) = 0. If f ′′(a) > 0 but f ′(a) 6 = 0, then the graph of f (x) is concave up at x = a but f (x) does not have a local min there.

III. Functions of Two Variables

  • Be able to compute overall, incremental, and instantaneous rates of change of a function of two variables. (WS 18A)
  • Be able to compute partial derivatives using all the derivative rules.
  • Know how to find the candidates for maxima and minima in a function of two variables. (Take both partial derivatives, set them equal to 0, and solve the resulting system of equations.)
  • Know the procedure for finding the best-fitting line for a set of data. (WS 18)

Step 1: Given n points (xi, yi), compute

∑ xi,

∑ yi,

∑ x^2 i ,

∑ y^2 i ,

∑ xiyi. Step 2: Use the sums from Step 1 to find the formula for the mean squared error function E(b, m). Step 3: Compute ∂E∂b and ∂E∂m. Step 4: Solve the system of equations ∂E∂b = 0 and ∂E∂m = 0 for m and b. These are the slope and y-intercept of the best-fitting line y = mx + b.

  • Know when it’s appropriate to take logs to make exponential data look linear. (WS 14)
  • Be able to convert a linear model for ln y into an exponential model for y.
  • Be able to solve a linear programming problem. (WS 19)

Step 1: Find the objective function. Step 2: Find the constraints. Step 3: Graph the feasible region and find its vertices. Step 4: Plug all vertices into the objective function. (The max and min of the objective function must occur at one of the vertices.)