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3 years ago

Find the radius of a circle whose circumference is 216 units, use 3.14 for π. r = 34.377 r = 34.395 r = 68.790

Mathematics

1 answer:

dlinn [17]3 years ago

7 0

Answer:

The value of radius is 34.395..

Step-by-step explanation:

The formula for finding the circumference of the circle is:

C=2πr.

Here we have given the values:

circumference = 216 units

π = 3.14.

r = ?

Substitute the values in the formula:

216 = 2(3.14)r

216=6.28r

Now divide both sides by 6.28.

We get,

216/6.28 = 6.28r/6.28

34.395=r

Thus the value of radius is 34.395...

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3 years ago

Read 2 more answers

Can anyone help<br> Me with this problem plz

seropon [69]

First you need common denominator
x/2 - 6/2 = 34/2
now , eliminate denominator
x - 6 = 34 add 6 to both sides and simplify
x=40

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3 years ago

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3 years ago

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Sphinxa [80]

Answer:

The probability that the mean life expectancy of the sample is less than X years is the p-value of $Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}$ , in which $\mu$ is the mean life expectancy, $\sigma$ is the standard deviation and n is the size of the sample.

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.

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

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.

Central Limit Theorem

The Central Limit Theorem establishes 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.

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Sample of size n:

This means that the z-score is now, by the Central Limit Theorem:

$Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}$

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2 years ago