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3 years ago

What is 0.64 as a fraction in lowest terms

2 answers:

6 0

Write the decimal number as a fraction
(over 1)
0.64 = 0.64 / 1

Multiplying by 1 to eliminate 2 decimal places
we multiply top and bottom by 2 10's

Numerator = 0.64 × 10 × 10 = 64

Denominator = 1 × 10 × 10 = 100

Numerator/denominator = 64 / 100

Simplifying our fraction

= 64/100

= 16/25

crimeas [40]3 years ago

5 0

$0.64\to two\ digits\ after\ the\ decimal\ point\ therefore\ are\ hundredths\\\\0.64=\frac{64}{100}=\frac{64:4}{100:4}=\boxed{\frac{16}{25}}$

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Answer:

We can use the z score formula given by:

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If we use this formula we got:

$z=\frac{21-20}{\frac{9.31}{\sqrt{18}}}= 0.456$

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And using a calculator, excel or the normal standard table and we have that:

$P(0.456$

Step-by-step explanation:

We assume this previous info: It is known that the amounts of time required for room-service delivery at a certain Marriott Hotel are Normally distributed with the average delivery time of 20 minutes.

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".

Solution to the problem

Let X the random variable that represent the delivery times of a population, and for this case we know the distribution for X is given by:

$X \sim N(20,9.31)$

Where $\mu=20$ and $\sigma=9.31$

Since the distribution for X is normal then the distribution for the sample mean $\bar X$ is given by:

$\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})$

And we can use the z score formula given by:

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

If we use this formula we got:

$z=\frac{21-20}{\frac{9.31}{\sqrt{18}}}= 0.456$

$z=\frac{25-20}{\frac{9.31}{\sqrt{18}}}= 2.279$

And using a calculator, excel or the normal standard table and we have that:

$P(0.456$

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