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Mathematics

1 answer:

KatRina [158]2 years ago

8 0

Answer:

A. -∞<x<∞ B. -∞<x<∞

Step-by-step explanation:

f(x) = 8x - 5

g(x) = (x+5)/8

(f·g)(x) = f(g(x)) = 8 ((x+5)/8) - 5 = x+5-5 = x

(g·f)(x) = g(f(x)) = ((8x-5)+5) / 8 = 8x/8 = x

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I need to know what is the find m<ACD

Pepsi [2]

Answer:

Step-by-step explanation:

if (AB and DC) parallels lines than the equation is alternate interior and therefore congruent to each other

8 0

2 years ago

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Because not all airline passengers show up for their reserved seat, an airline sells 125 tickets for a flight that holds only 12

melamori03 [73]

Answer:

98.75% probability that every passenger who shows up can take the flight

Step-by-step explanation:

For each passenger who show up, there are only two possible outcomes. Either they can take the flight, or they do not. The probability of a passenger taking the flight is independent from other passenger. So the binomial probability distribution is used to solve this question.

However, we are working with a large sample. So i am going to aproximate this binomial distribution to the normal.

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 $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .