I need help with this math challenge! Please

Mathematics

2 answers:

Dennis_Churaev [7]3 years ago

8 0

i need to see what problem your doing and then i can totally help you!!!!

tester [92]3 years ago

6 0

If I've understood this correct, n bisects (cuts in half) the 44yd line? So we get a triangle like this and perform pythagorus theorem.

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A box of jerseys for a pick-up game of basketball contains 9 extra-large jerseys, 6 large jerseys, and 5 medium jerseys. If you

aleksley [76]

Answer:

1/114 or 0.008772

Step-by-step explanation:

I am not very sure, my answer seems unlikely, but here's what I think:

There are 20 jerseys in the box to begin with, and 5 medium jerseys that you can have.

Therefore, the probability of you randomly grabbing a medium sized jersey is 5/20 or 1/4.

After taking out one medium sized jersey, there are 19 jerseys in the box and 4 medium jerseys you can pick from.

The probability of you randomly grabbing a medium sized jersey is 4/19.

After taking out another medium sized jersey, there are 18 jerseys left in the box and 3 medium jerseys you can pick from.

The probability of you randomly grabbing a medium sized jersey is 3/18.

To get the answer, you do 1/4 * 4/19 * 3/18, and get 1/114, or 0.00877192982.

If you round that to the nearest millionth, it's 0.008772

Don't judge me, it might not be correct.

4 0

3 years ago

A report indicated that 37% of adults had received a bogus email intended to steal personal information. Suppose a random sample

fiasKO [112]

Answer:

5.05% probability that no more than 34% had received such an email.

Step-by-step explanation:

We use the binomial approximation to the normal to solve this problem.

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

$E(X) = np$

The standard deviation of the binomial distribution is:

$\sqrt{V(X)} = \sqrt{np(1-p)}$

Normal probability distribution

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

When we are approximating a binomial distribution to a normal one, we have that $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .