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Art [367]
3 years ago
9

What is 3.142857 rounded three decimal places

Mathematics
2 answers:
Murljashka [212]3 years ago
4 0

Answer:

3.143

Step-by-step explanation:

Since you're rounded it to the third decimal, you look at the fourth one. And since the fourth one is 8, ur going round 2, which is the third decimal to 3.

kati45 [8]3 years ago
4 0

Answer:

The answer is below

Step-by-step explanation:

In this question, to round three decimal place, we need to count three numbers after the dot.

Here..

the three numbers are 142

so after that we round it, so first of all we ignore 1 and, and focus on the number 2 and 4.

and if the number is below 5, it is rounded to the last number, but if the number is 5 or more than it, then we round it to the next number.

For example

142 - here we have 2, which is below 5, so we round it to '140'

where as if we have..

147 - here we have 7, which is above 7, so we round it to '150'

____________________________________________________________

So in this problem we round 142, so the number 2 is below 5 so it is round to 140

therefore the answer is - 3.14

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The weight of crackers in a box is stated to be 16 ounces. The amount that the packaging machine puts in the boxes is believed t
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Answer:

99.99% probability that the mean weight of a 50-box case of crackers is above 16 ounces

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}}.

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

In this problem, we have that:

\mu = 16.15, \sigma = 0.3, n = 50, s = \frac{0.3}{\sqrt{50}} = 0.0424

What is the probability that the mean weight of a 50-box case of crackers is above 16 ounces?

This is 1 subtracted by the pvalue of Z when X = 16. So

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

By the Central Limit Theorem

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

Z = \frac{16 - 16.15}{0.0424}

Z = -3.54

Z = -3.54 has a pvalue of 0.0001

1 - 0.0001 = 0.9999

99.99% probability that the mean weight of a 50-box case of crackers is above 16 ounces

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Step-by-step explanation:

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