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Afina-wow [57]
4 years ago
12

Farmer McCoy can plant either corn or soybeans. The probabilities that the next harvest prices will go up, stay the same, or go

down are .25, .30 and .45 respectively. If the prices go up, the corn crop will give a net profit of $30,000 and the soybeans will give a net profit of $10,000. If the prices remain unchanged, McCoy will have $0 profit/loss for both crops. But if the prices go down, the corn and soybeans crops will sustain losses of $35,000 and $5,000 respctively. (A) Represent McCoy's problem as a decision tree. (B) Which crop should McCoy plant?
Mathematics
1 answer:
Snezhnost [94]4 years ago
4 0

Answer:

McCoy should plant soybeans

Step-by-step explanation:

Thinking process:

Let the two crops be corn and soybeans as indicated.

The profit margin for corn will be $ 30 000. However, the loss will be:

$ 35 000 - $ 30 000 = $ 5 000

For the soybean, the  profit margin will be $ 10 000.

The loss will be $ 5 000

The net balance will be given as: $ 5 000 - $ 10 000 = - $ 5 000. (This represents a gain)

Thus, soybean will be more profitable.

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Answer:

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Step-by-step explanation:

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3 years ago
if 2 and 4 are factors of a number, is 8 also a factor of that number? I know it's false ( 12 is a multiple of 2 and 4 but not 8
AURORKA [14]

Answer:

It would be false because 2 and 4 are factors which simply mean they can multiply togeher to get another number

Step-by-step explanation:


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4 years ago
Let Y1, Y2, . . . , Yn be independent, uniformly distributed random variables over the interval [0, θ]. Let Y(n) = max{Y1, Y2, .
Anettt [7]

Answer:

a) F(y) = 0, y

F(y) = \frac{y}{\theta} , 0 \leq y \leq \theta

F(y)= 1, y>1

b) f_{Y_{(n)}} = \frac{d}{dy} (\frac{y}{\theta})^n = n \frac{y^{n-1}}{\theta^n}, 0 \leq y \leq \theta

f_{Y_{(n)}} =0 for other case

c) E(Y_{(n)}) = \frac{n}{\theta^n} \frac{\theta^{n+1}}{n+1}= \theta [\frac{n}{n+1}]

Var(Y_{(n)}) =\theta^2 [\frac{n}{(n+1)(n+2)}]

Step-by-step explanation:

We have a sample of Y_1, Y_2,...,Y_n iid uniform on the interval [0,\theta] and we want to find the cumulative distribution function.

Part a

For this case we can define the CDF for Y_i , i =1,2.,,,n like this:

F(y) = 0, y

F(y) = \frac{y}{\theta} , 0 \leq y \leq \theta

F(y)= 1, y>1

Part b

For this case we know that:

F_{Y_{(n)}} (y) = P(Y_{(n)} \leq y) = P(Y_1 \leq y,....,Y_n \leq y)

And since are independent we have:

F_{Y_{(n)}} (y) = P(Y_1 \leq y) * ....P(Y_n \leq y) = (\frac{y}{\theta})^n

And then we can find the density function calculating the derivate from the last expression and we got:

f_{Y_{(n)}} = \frac{d}{dy} (\frac{y}{\theta})^n = n \frac{y^{n-1}}{\theta^n}, 0 \leq y \leq \theta

f_{Y_{(n)}} =0 for other case

Part c

For this case we can find the mean with the following integral:

E(Y_{(n)}) = \frac{n}{\theta^n} \int_{0}^{\theta} y y^{n-1} dy

E(Y_{(n)}) = \frac{n}{\theta^n} \int_{0}^{\theta} y^n dy

E(Y_{(n)}) = \frac{n}{\theta^n} \frac{y^{n+1}}{n+1} \Big|_0^{\theta}

And after evaluate we got:

E(Y_{(n)}) = \frac{n}{\theta^n} \frac{\theta^{n+1}}{n+1}= \theta [\frac{n}{n+1}]

For the variance first we need to find the second moment like this:

E(Y^2_{(n)}) = \frac{n}{\theta^n} \int_{0}^{\theta} y^2 y^{n-1} dy

E(Y^2_{(n)}) = \frac{n}{\theta^n} \int_{0}^{\theta} y^{n+1} dy

E(Y^2_{(n)}) = \frac{n}{\theta^n} \frac{y^{n+2}}{n+2} \Big|_0^{\theta}

And after evaluate we got:

E(Y^2_{(n)}) = \frac{n}{\theta^n} \frac{\theta^{n+2}}{n+2}= \theta^2 [\frac{n}{n+2}]

And the variance is given by:

Var(Y_{(n)}) = E(Y^2_{(n)}) - [E(Y_{(n)})]^2

And if we replace we got:

Var(Y_{(n)}) =\theta^2 [\frac{n}{n+2}] -\theta^2 [\frac{n}{n+1}]^2

Var(Y_{(n)}) =\theta^2 [\frac{n}{n+2} -(\frac{n}{n+1})^2]

And after do some algebra we got:

Var(Y_{(n)}) =\theta^2 [\frac{n}{(n+1)(n+2)}]

3 0
4 years ago
Olive’s solar powered scooter travels at a rate of 30 miles per hour. What equation can she use to calculate her distance with r
kirza4 [7]
Suppose time Olive is traveling is x hours.
distance=speed×time
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4 years ago
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What is 1/30 as a decimal
Damm [24]

Answer:

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Step-by-step explanation:

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