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3 years ago

an equilateral triangle has height 26 cm what is the length of each side of the triangle to the nearest centimeter

1 answer:

4 0

H = 26 is the given height of the equilateral triangle
s = unknown side length of the equilateral triangle

The formula to use is
s = (2/3)*sqrt(3)*h
which helps tie together the side length s and the height h

Plug in the given height h = 26 and we get...
s = (2/3)*sqrt(3)*h
s = (2/3)*sqrt(3)*26
s = 30.0222
That rounds to 30

Answer: 30

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3 years ago

Help Please!! I am not sure what to do?

Iteru [2.4K]

Answer:

10 < $\sqrt{111}$ < 11

Step-by-step explanation:

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3 years ago

A practice law exam has 100 questions, each with 5 possible choices. A student took the exam and received 13 out of 100.If the s

Cloud [144]

Answer:

$z=\frac{13-20}{4}=-1.75$

Assuming:

H0: $\mu \geq 20$

H1: $\mu$

$p_v = P(Z$

Step-by-step explanation:

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".

Let X the random variable of interest (number of correct answers in the test), on this case we now that:

$X \sim Binom(n=100, p=0.2)$

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:

$nCx=\frac{n!}{(n-x)! x!}$

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

$np=100*0.2=20 \geq 10$

$n(1-p)=20*(1-0.2)=16 \geq 10$

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:

$E(X)=np=100*0.2=20$

$\sigma=\sqrt{np(1-p)}=\sqrt{100*0.2(1-0.2)}=4$

So we can approximate the random variable X like this:

$X\sim N(\mu =20, \sigma=4)$

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