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DiKsa [7]
3 years ago
11

Two 2 1/2 inch plastic strips and two 5 1/3 inch plastic strips are used to form a rectangle. What is the perimeter of the recta

ngle?
Mathematics
2 answers:
svp [43]3 years ago
5 0
In this question the given information's should be closely noted. The length and width of the perimeter are already given. Based on those information's the answer to the question can be easily deduced.
Length of the rectangle = 2 1/2 inch
                                       = 5/2 inch
Width of the rectangle = 5 1/3 inch
                                         = 16/3 inch
Then
Perimeter of a rectangle = 2 ( Length + Width)
                                        = 2 [(5/2) + (16/3)]
                                         = 2 [ (45 + 32)/6]
                                         = 2 * (77/6)
                                         = 77/3 inch
                                         = 25 2/3 inch
So the perimeter of the rectangle in question is 25 2/3 inch. I hope the procedure is clear to you.
m_a_m_a [10]3 years ago
3 0
<h2>Answer</h2>

The perimeter of the rectangle is 15\frac{2}{3}

<h2>Explanation</h2>

To solve this, we are going to use the formula for the perimeter of a rectangle:

P=2(w+l)

where

P is the perimeter of the rectangle

w is the width of the rectangle

l is the length of the rectangle

We can infer from our problem the the shorter strips are 2\frac{1}{2} inches, so w=2\frac{1}{2}. That leaves us with l=5\frac{1}{3}. Let's replace those values in our formula to find P:

P=2(w+l)

P=2(2\frac{1}{2}+5\frac{1}{3})

P=2(\frac{5}{2} +\frac{16}{3} )

P=2(\frac{47}{6} )

P=\frac{47}{3}

P=15\frac{2}{3}

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You have a coin that is not weighted evenly and therefore is not a fair coin. Assume the true probability of getting heads when
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Answer:

X \sim Binom(n=157, p=0.52)

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!}

And we want this probability:

P(X

And we can use the following Excel code to find the exact answer:

"=BINOM.DIST(75,157,0.52,TRUE)"

And we got 0.1633

The other way to solve the problem is using the normal approximation

We need to check the conditions in order to use the normal approximation.

np=157*0.52=81.64  \geq 10

n(1-p)=157*(1-0.52)=75.36 \geq 10

So we see that we satisfy the conditions and then we can apply the approximation.

If we appply the approximation the new mean and standard deviation are:

E(X)=np=157*0.52=81.64

\sigma=\sqrt{np(1-p)}=\sqrt{157*0.52(1-0.52)}=6.26

We want this probability:

P(X

And using the continuity correction we have this:

P(X

We can use the z score given by this formula Z=\frac{x-\mu}{\sigma}.

P(X< 76.5)=P(\frac{X-\mu}{\sigma}< \frac{76.5-81.64}{6.26})=P(Z < -0.821)=0.206

Step-by-step explanation:

Previous concepts

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".

Solution to the problem

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

X \sim Binom(n=157, p=0.52)

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!}

And we want this probability:

P(X

And we can use the following Excel code to find the exact answer:

"=BINOM.DIST(75,157,0.52,TRUE)"

And we got 0.1633

The other way to solve the problem is using the normal approximation

We need to check the conditions in order to use the normal approximation.

np=157*0.52=81.64  \geq 10

n(1-p)=157*(1-0.52)=75.36 \geq 10

So we see that we satisfy the conditions and then we can apply the approximation.

If we appply the approximation the new mean and standard deviation are:

E(X)=np=157*0.52=81.64

\sigma=\sqrt{np(1-p)}=\sqrt{157*0.52(1-0.52)}=6.26

We want this probability:

P(X

And using the continuity correction we have this:

P(X

We can use the z score given by this formula Z=\frac{x-\mu}{\sigma}.

P(X< 76.5)=P(\frac{X-\mu}{\sigma}< \frac{76.5-81.64}{6.26})=P(Z < -0.821)=0.206

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Percent:

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0.12 x 100 = 12

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2 years ago
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