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grigory [225]
1 year ago
9

Let g(x)=log_2x1. find g(5)2. find g(-3)3. find g^-1(x)4. find g^-1(-3)

Mathematics
1 answer:
Olin [163]1 year ago
4 0
g(x)=\log _2x

You evaluate the equation in the given values of x:

\log _ba=\frac{\log a}{\log b}

1. g(5)\begin{gathered} g(5)=\log _25 \\ g(5)=\frac{\log 5}{\log 2}=2.321 \end{gathered}g(5)=2.3212. g(-3)\begin{gathered} g(-3)=\log _2(-3) \\ g(-3)=\frac{\log (-3)}{\log 2}=\text{undefined} \end{gathered}

The logarithm of a negative number is undefined

3. g^-1(x)

To find the inverse function you:

-write the function with x and y:

\begin{gathered} g(x)=\log _2x \\ y=\log _2x \end{gathered}

-Solve variable x:

knowing that:

\begin{gathered} \log _ba=c \\ b^c=a \end{gathered}\begin{gathered} y=\log _2x \\  \\ 2^y=x \end{gathered}

- Change the x for (g^-1(x)) and the y for x:

g^{-1}(x)=2^x4.g^-1(-3)​

As:

n^{-m}=\frac{1}{n^m}

\begin{gathered} g^{-1}(-3)=2^{-3} \\  \\ =\frac{1}{2^3}=\frac{1}{8} \end{gathered}

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Step-by-step explanation:

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Vera_Pavlovna [14]

Answer:

0.8254 = 82.54% probability that the mean of this sample is between 19.25 hours and 21.0 hours

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 normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score 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 p-value, we get the probability that the value of the measure is greater than X.

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

Mean of 20 hours, standard deviation of 6:

This means that \mu = 20, \sigma = 6

Sample of 150:

This means that n = 150, s = \frac{6}{\sqrt{150}}

What is the probability that the mean of this sample is between 19.25 hours and 21.0 hours?

This is the p-value of Z when X = 21 subtracted by the p-value of Z when X = 19.5. So

X = 21

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

By the Central Limit Theorem

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

Z = \frac{21 - 20}{\frac{6}{\sqrt{150}}}

Z = 2.04

Z = 2.04 has a p-value of 0.9793

X = 19.5

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

Z = \frac{19.5 - 20}{\frac{6}{\sqrt{150}}}

Z = -1.02

Z = -1.02 has a p-value of 0.1539

0.9793 - 0.1539 = 0.8254

0.8254 = 82.54% probability that the mean of this sample is between 19.25 hours and 21.0 hours

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