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Semenov [28]
3 years ago
10

What is g^-1(x)? What is the domain of g^-1(x)? Please help!! It’ll be greatly appreciated!!

Mathematics
1 answer:
Ymorist [56]3 years ago
6 0

Answer:  g^{-1}(x) = \frac{1-4x}{x}

Domain of the inverse is any real number but x cannot equal zero

Domain in set builder notation = \{x | x\in\mathbb{R} , \ x \ne 0\}

Domain in interval notation = (-\infty, 0) \cup (0, \infty)

================================================

Let's make h(x) be the inverse of g(x)

g(x) = 1/(x+4) is the same as y = 1/(x+4).

To find the inverse, we swap x and y, then solve for y like so....

y = 1/(x+4)

x = 1/(y+4) .... x and y swap

x(y+4) = 1

xy+4x = 1

xy = 1-4x

y = (1-4x)/x

h(x) = (1-4x)/x is the inverse of g(x)

We can verify this by showing that g(h(x)) = x and h(g(x)) = x. I'll leave that for you to confirm.

The domain of h(x) is the set of real numbers x such that x cannot be 0. So x can be anything but 0. In set builder notation, we would say \{x | x\in\mathbb{R} , \ x \ne 0\} and in interval notation that is (-\infty, 0) \cup (0, \infty)

We kick out x = 0 so that  (1-4x)/x doesn't have any division by zero errors.

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ICE Princess25 [194]

Answer:

The probability is 0.789

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

Problems of normally distributed samples are 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.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

In this problem, we have that:

\sigma = 16, n = 400, s = \frac{16}{\sqrt{400}} = 0.8

Find the probability that the mean age of the individuals sampled is within one year of the mean age for all individuals in the city.​

Using \mu = 30, this is the pvalue of Z when X = 31 subtracted by the pvalue of Z when X = 29. So

X = 31

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

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{31 - 30}{0.8}

Z = 1.25

Z = 1.25 has a pvalue of 0.8944

X = 29

Z = \frac{X - \mu}{s}

Z = \frac{29 - 30}{0.8}

Z = -1.25

Z = -1.25 has a pvalue of 0.1056

0.8944 - 0.1056 = 0.7888

Rounded to three decimal places, 0.789

The probability is 0.789

4 0
3 years ago
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Answer:

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