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marshall27 [118]
3 years ago
11

Number of passengers who arrive at the platform in an Amtrack train station for the 2 pm train on a Saturday is a random variabl

e with a mean of 180 and a standard deviation of 25. With what probability can we assert that there will be between 80 and 280 passengers?
Mathematics
1 answer:
Svetradugi [14.3K]3 years ago
5 0

Answer:

P(80

And we can find this probability with this difference:

P(-4

And in order to find these probabilities we can use tables for the normal standard distribution, excel or a calculator.  

P(-4

Step-by-step explanation:

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 number of passengers who arrive at the platform of a population, and for this case we know the following info

Where \mu=180 and \sigma=25

We are interested on this probability

P(80

For this case we can assume that the random variable is normally distributed.

And the best way to solve this problem is using the normal standard distribution and the z score given by:

z=\frac{x-\mu}{\sigma}

If we apply this formula to our probability we got this:

P(80

And we can find this probability with this difference:

P(-4

And in order to find these probabilities we can use tables for the normal standard distribution, excel or a calculator.  

P(-4

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A) 3x = 18<br> b) 2x=9<br> c) =7<br> d) x/5= 7
lilavasa [31]

Answer:

a) 6

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c) unsure due to not knowing the whole problem

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Step-by-step explanation:

3 0
2 years ago
The amount of coffee that a filling machine puts into an 8 dash ounce 8-ounce jar is normally distributed with a mean of 8.2 oun
Inessa [10]

Answer:

73.3% probability that the sampling error made in estimating the mean amount of coffee for all 8 dash ounce 8-ounce jars by the mean of a random sample of 100​ jars, will be at most 0.02​ ounce

Step-by-step explanation:

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

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 question, we have that:

\mu = 8.2, \sigma = 0.18, n = 100, s = \frac{0.18}{\sqrt{100}} = 0.018

What is the probability that the sampling error made in estimating the mean amount of coffee for all 8 dash ounce 8-ounce jars by the mean of a random sample of 100​ jars, will be at most 0.02​ ounce

That is, probability of the sample mean between 8.2-0.02 = 8.18 and 8.2 + 0.02 = 8.22, which is the pvalue of Z when X = 8.22 subtracted by the pvalue of Z when X = 8.18.

X = 8.22

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

By the Central Limit Theorem

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

Z = \frac{8.22 - 8.2}{0.018}

Z = 1.11

Z = 1.11 has a pvalue of 0.8665.

X = 8.18

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

Z = \frac{8.18 - 8.2}{0.018}

Z = -1.11

Z = -1.11 has a pvalue of 0.1335.

0.8665 - 0.1335 = 0.7330

73.3% probability that the sampling error made in estimating the mean amount of coffee for all 8 dash ounce 8-ounce jars by the mean of a random sample of 100​ jars, will be at most 0.02​ ounce

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vredina [299]

Answer:

It looks like (-1, ∞)

Step-by-step explanation:

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