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Goryan [66]
3 years ago
12

Find the area of the figure. Round to the nearest tenth if necessary.

Mathematics
1 answer:
Sladkaya [172]3 years ago
5 0

Answer:

The area of the figure is 193.1 m

Step-by-step explanation:

  1. The <u>figure can be divided in two</u>: a rectangle with a with of 11.1m and a lenght of 15.3 m; and a triangle with a base that measure 11.1 m and  the height of (19.5 - 15.3 = 4.2 m).
  2. The area of the rectangle can be calculated as follows: area=with\times{height}. Then, the rectabgle area equals 11.1\times15.3=169.83m.
  3. The area of a triangle can be calculated as area=\frac{base\times{height}}{2}. Then, the triangle area equals \frac{11.1\times{4.2}}{2} =23.31.
  4. The sum of both areas equals the area of the figure. Then, the area of the figure equals 169.83+23.31=193.14≅193.1
  5. See the picture attached to see en detail the decomposition of the figure into a triangle and a rectangle.

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A machine has 12 identical components which function independently. The probability that a component will fail is 0.2. The machi
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Answer:

P(X>3) =1- P(X\leq 3) = 1-[P(X=0)+P(X=1) +P(X=2) +P(X=3)]

And if we find the individual probabilities we got:

P(X=0)=(12C0)(0.2)^0 (1-0.2)^{12-0}=0.0687

P(X=1)=(12C1)(0.2)^1 (1-0.2)^{12-1}=0.2062

P(X=2)=(12C2)(0.2)^2 (1-0.2)^{12-2}=0.2835

P(X=3)=(12C3)(0.2)^3 (1-0.2)^{12-3}=0.2362

And if we replace we got:

P(X>3) =1- P(X\leq 3) = 1-[0.0687+0.2062 +0.2835 +0.2362]=0.20543

Step-by-step explanation:

Previous concepts

A Bernoulli trial is "a random experiment with exactly two possible outcomes, "success" and "failure", in which the probability of success is the same every time the experiment is conducted". And this experiment is a particular case of the binomial experiment.

The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".

The probability mass function for the Binomial distribution is given as:  

P(X)=(nCx)(p)^x (1-p)^{n-x}  

Where (nCx) means combinatory and it's given by this formula:  

nCx=\frac{n!}{(n-x)! x!}  

The complement rule is a theorem that provides a connection between the probability of an event and the probability of the complement of the event. Lat A the event of interest and A' the complement. The rule is defined by: P(A)+P(A') =1

Solution to the problem

Let X the random variable of interest, on this case we now that:

X \sim Binom(n=12, p=0.2)

And we want to find this probability:

P(X > 3)

And we can use the complement rule and we got:

P(X>3) =1- P(X\leq 3) = 1-[P(X=0)+P(X=1) +P(X=2) +P(X=3)]

And if we find the individual probabilities we got:

P(X=0)=(12C0)(0.2)^0 (1-0.2)^{12-0}=0.0687

P(X=1)=(12C1)(0.2)^1 (1-0.2)^{12-1}=0.2062

P(X=2)=(12C2)(0.2)^2 (1-0.2)^{12-2}=0.2835

P(X=3)=(12C3)(0.2)^3 (1-0.2)^{12-3}=0.2362

And if we replace we got:

P(X>3) =1- P(X\leq 3) = 1-[0.0687+0.2062 +0.2835 +0.2362]=0.20543

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