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Taya2010 [7]
2 years ago
5

If Ana devotes all her time to making fudge, she can make 3 pounds of fudge an hour, and if he devotes all her time to making to

ffee, she can make 2 pounds of toffee an hour. If Leo devotes all his time to making fudge, he can make 4 pounds of fudge an hour, and if he devotes all his time to making toffee, he can make 5 pounds of toffee an hour. According to The Principle of Comparative Advantage, Ana and Leo will be able to produce more overall if:
Mathematics
1 answer:
lara [203]2 years ago
7 0

Answer: If Ana produce more furge and Leo produce more toffee.

Step-by-step explanation:

Comparative advantage: A country or a person has a comparative advantage in producing a commodity if the opportunity cost of producing that commodity is lower in that country as compared to the other country.

Here Ana or Leo will gain comparative advantage only when they are selling the good they are specializing in and they would specialize in that good which would have lower opportunity cost for them.

(a) For Ana who devoted all of her time to making either 3 pounds of fudge or 2 pounds of toffee,

the opportunity cost for making 1 pound of furge is = 2/3 = 0.66

the opportunity cost for making 1 pound of toffee is = 3/2 = 1.5

(b) For Leo who devoted all of her time to making either 4 pounds of fudge or 5 pounds of toffee,

the opportunity cost for making 1 pound of furge is = 5/4 = 1.25

the opportunity cost for making 1 pound of toffee is = 4/5 = 0.8

Above calculations clearly shows that Ana has a comparative advantage in producing furge because opportunity cost of making furge is lower than the Leo, so he devotes most of his time to produce furge.

Whereas Leo has a comparative advantage in producing Toffee because opportunity cost of making toffee is lower than the Ana, so he devotes most of his time to produce toffee.

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Explain when the median of a data set is a better measure of center than the mean
vlada-n [284]

The dot plot or histogram will be skewed.

The mean is pulled up or down toward the tail.

The mean is affected more than the median.


Sample Response: When there is an outlier in the data set, the dot plot or histogram will be skewed. In a skewed representation, the mean is pulled up or down toward the tail of the data. Therefore, skewed data affects the mean more than the median.

5 0
2 years ago
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How many terms are in the algebraic expression -7 + 12x4 - 5y8 + x?
Mazyrski [523]

Answer:

4

Step-by-step explanation:

Each mix of numbers and letters that is separated by a + or a - is a term.

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2 years ago
A television is 28.5 inches wide and 16 inches long.
Umnica [9.8K]

Answer:

  33 in

Step-by-step explanation:

The Pythagorean theorem tells you ...

  diagonal² = length² +width²

  diagonal² = (16 in)² +(28.5 in)² = 1068.25 in²

  diagonal = √(1068.25 in²) ≈ 32.684 in

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2 years ago
The weight of a person on or above the surface of the earth varies inversely as the square of the distance the person is from th
jeyben [28]
Weight = k/(distance)². Let's find the value of k when distance = earth radius:

180 = k/(3900)² → k = 180 x 3900² → k = 2,737,800,000

If he is at 325 miles ABOVE the earth, the distance becomes: 3,900+325=4,225 miles and his weight becomes:

Weight = k/(distance)² → Weight = 2,737,800,000/(4225)² = 153.37

Weight = 153.37 lb

8 0
2 years ago
In constructing a 95 percent confidence interval, if you increase n to 4n, the width of your confidence interval will (assuming
Damm [24]

Answer:

about 50 percent of its former width.

Step-by-step explanation:

Let's assume that our parameter of interest is given by \theta and in order to construct a confidence interval we can use the following formula:

\hat \theta \pm ME(\hat \theta)

Where \hat \theta is an estimator for the parameter of interest and the margin of error is defined usually if the distribution for the parameter is normal as:

ME = z_{\alpha} SE

Where z_{\alpha/2} is a quantile from the normal standard distribution that accumulates \alpha/2 of the area on each tail of the distribution. And SE represent the standard error for the parameter.

If our parameter of interest is the population proportion the standard of error is given by:

SE= \frac{\hat p (1-\hat p)}{n}

And if our parameter of interest is the sample mean the standard error is given by:

SE = \frac{s}{\sqrt{n}}

As we can see the standard error for both cases assuming that the other things remain the same are function of n the sample size and we can write this as:

SE = f(n)

And since the margin of error is a multiple of the standard error we have that ME = f(n)

Now if we find the width for a confidence interval we got this:

Width = \hat \theta + ME(\hat \theta) -[\hat \theta -ME(\hat \theta)]

Width = 2 ME (\hat \theta)

And we can express this as:

Width =2 f(n)

And we can define the function f(n) = \frac{1}{\sqrt{n}} since as we can see the margin of error and the standard error are function of the inverse square root of n. So then we have this:

Width_i= 2 \frac{1}{\sqrt{n}}

The subscript i is in order to say that is with the sample size n

If we increase the sample size from n to 4n now our width is:

Width_f = 2 \frac{1}{\sqrt{4n}} =2 \frac{1}{\sqrt{4}\sqrt{n}} =\frac{2}{2} \frac{1}{\sqrt{n}} =\frac{1}{\sqrt{n}} =\frac{1}{2} Width_i

The subscript f is in order to say that is the width for the sample size 4n.

So then as we can see the width for the sample size of 4n is the half of the wisth for the width obtained with the sample size of n. So then the best option for this case is:

about 50 percent of its former width.

7 0
2 years ago
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