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Novosadov [1.4K]
1 year ago
9

F(x)=-3+|x-11| reflection across the Y axis

Mathematics
1 answer:
qaws [65]1 year ago
6 0

The function after the reflection is f'(x) = -3 + |-x - 11|

<h3>How to determine the function after the reflection?</h3>

The function is given as:

f(x) = -3 + |x - 11|

The function after the reflection across the y-axis is represented as:

f'(x) = f(-x)

So, we have:

f(-x) = -3 + |-x - 11|

This gives

f'(x) = -3 + |-x - 11|

Hence, the function after the reflection is f'(x) = -3 + |-x - 11|

Read more about function transformation at:

brainly.com/question/1548871

#SPJ1

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What fraction is equal to .66?<br><br> A.1/3<br><br> B.1/5<br><br> C.2/3<br><br> D.2/4
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Each contestant in the Hunger Games must be trained to compete. Suppose that the time it takes to train a contestant has mean 5
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Answer:

11.51% probability that it will take less than 450 days to train all the contestants.

Step-by-step explanation:

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

Normal probability distribution

When the distribution is normal, we use 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.

For the sum of n variables, the mean is \mu*n and the standard deviation is s = \sigma\sqrt{n}

In this question:

n = 100, \mu = 100*5 = 500, s = 4\sqrt{100} = 40

Approximate the probability that it will take less than 450 days to train all the contestants.

This is the pvalue of Z when X = 450.

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

By the Central Limit Theorem

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

Z = \frac{450 - 500}{40}

Z = -1.2

Z = -1.2 has a pvalue of 0.1151

11.51% probability that it will take less than 450 days to train all the contestants.

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