The Marriage Problem There is an infamous problem from mathematics that attempts to quantify the number of potential mates one should date before choosing one’s “true love.” The function L ( x ) = − x ln x represents the probability of finding the ideal mate after rejecting the first x proportion of potential mates. For example, if you reject the first 20 % = 0.20 of individuals you date, the probability of finding the ideal mate to be greater than 0.332 and you are only willing to date up to 20 individuals, you should reject the first 0.2 ( 20 ) = 4 individuals before attempting to decide on the ideal mate. Presumably, you are using those first 4 individuals to help you decide which traits you value in a mate. Determine and interpret L ( 0.1 ) . Determine and interpret L ( 0.6 ) . What is the domain of L ? Graph L = L ( x ) over the domain. Judging on the basis of the approach suggested by the model, what is the value of x that maximizes L ? What is the highest probability of finding the ideal mate?
The Marriage Problem There is an infamous problem from mathematics that attempts to quantify the number of potential mates one should date before choosing one’s “true love.” The function L ( x ) = − x ln x represents the probability of finding the ideal mate after rejecting the first x proportion of potential mates. For example, if you reject the first 20 % = 0.20 of individuals you date, the probability of finding the ideal mate to be greater than 0.332 and you are only willing to date up to 20 individuals, you should reject the first 0.2 ( 20 ) = 4 individuals before attempting to decide on the ideal mate. Presumably, you are using those first 4 individuals to help you decide which traits you value in a mate. Determine and interpret L ( 0.1 ) . Determine and interpret L ( 0.6 ) . What is the domain of L ? Graph L = L ( x ) over the domain. Judging on the basis of the approach suggested by the model, what is the value of x that maximizes L ? What is the highest probability of finding the ideal mate?
Solution Summary: The author calculates the probability of finding the ideal mate after rejecting the first x proportions of potential mates.
The Marriage Problem There is an infamous problem from mathematics that attempts to quantify the number of potential mates one should date before choosing one’s “true love.” The function
L
(
x
)
=
−
x
ln
x
represents the probability of finding the ideal mate after rejecting the first
x
proportion of potential mates. For example, if you reject the first
20
%
=
0.20
of individuals you date, the probability of finding the ideal mate to be greater than
0.332
and you are only willing to date up to
20
individuals, you should reject the first
0.2
(
20
)
=
4
individuals before attempting to decide on the ideal mate. Presumably, you are using those first
4
individuals to help you decide which traits you value in a mate.
Determine and interpret
L
(
0.1
)
.
Determine and interpret
L
(
0.6
)
.
What is the domain of
L
?
Graph
L
=
L
(
x
)
over the domain.
Judging on the basis of the approach suggested by the model, what is the value of
x
that maximizes
L
? What is the highest probability of finding the ideal mate?
the correct answer is Ccould you please show me how to do it using the residue theorem
Use the information to find and compare Δy and dy. (Round your answers to four decimal places.)
y = x4 + 7 x = −3 Δx = dx = 0.01
Δy =
dy =
4. A car travels in a straight line for one hour. Its velocity, v, in miles per hour at six minute intervals is shown
in the table. For each problem, approximate the distance the car traveled (in miles) using the given method,
on the provided interval, and with the given number of rectangles or trapezoids, n.
Time (min) 0 6 12 18|24|30|36|42|48|54|60
Speed (mph) 0 10 20 40 60 50 40 30 40 40 65
a.) Left Rectangles, [0, 30] n=5
b.) Right Rectangles, [24, 42] n=3
c.) Midpoint Rectangles, [24, 60] n=3
d.) Trapezoids, [0, 24] n=4
Chapter 4 Solutions
Pearson eText for Precalculus: Concepts Through Functions, A Right Triangle Approach to Trigonometry -- Instant Access (Pearson+)
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