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3 years ago

Please help I know the answer but I need to know the work please explain Answer is b

Mathematics

1 answer:

zhenek [66]3 years ago

7 0

Answer:

$\huge\boxed{\sf B.}$

Step-by-step explanation:

Geometric Mean is a type of average in which we multiply the number given and put a square root on it.

<u>Geometric Mean of 4 and 7:</u>

$\sf \sqrt{4*7} \\\\\sqrt{2^2*7} \\\\= 2\sqrt{7} \\\\\rule[225]{225}{2}$

Hope this helped!

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2 years ago

The question is: "Without actually graphing, describe how the graph of y = ( -2^(x+17) ) - 4.3 is related to the graph of y = 2^

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The function has been flipped due to the negative in front.

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Step-by-step explanation:

When functions are transformed there are a few simple rules:

Adding/subtracting inside the parenthesis to the input shifts the function left(+) and right(-).
Adding/subtracting outside the parenthesis to the output shifts the function up(+) and down(-).
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3 years ago

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Alenkinab [10]

Answer:

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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 $s = \frac{\sigma}{\sqrt{n}}$ .