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Andrew [12]
3 years ago
5

Is it possible for two linear functions whose graph are parallel to have the same y-intercept

Mathematics
1 answer:
soldier1979 [14.2K]3 years ago
5 0
If you have e two linear functions and on a graph they are parallel that means they have the same slope with different y intercepts. If they are parallel and have the same y intercept then they would be the same graph. So no it’s not possible because there would not be two different graphs/functions; they would be exactly the same.
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Step-by-step explanation:

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2 years ago
You have a coin that is not weighted evenly and therefore is not a fair coin. Assume the true probability of getting heads when
Alexandra [31]

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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S H O W Y O U R W O R K
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Answer:

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Step-by-step explanation:

That would be

-34.44 + 49.44

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= 15 degrees

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4 years ago
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