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pashok25 [27]
2 years ago
15

Pls help I need a good grade 46=-6t-8 Show ur work

Mathematics
1 answer:
m_a_m_a [10]2 years ago
5 0
Add 8 to 46. Then divide 54/8 to get 6.75 and t=6.75
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Please help me solve this priblem
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and the volume is 5400
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Joe is riding his bicycle. He rides for 3 hours at a speed of 4.8 kilometers per hour. For how many kilometers does he ride?
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14.4km

Step-by-step explanation:

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A study investigating the relationship between age and annual medical expenses randomly samples 400 individuals in a city. It is
ICE Princess25 [194]

Answer:

The probability is 0.789

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:

\sigma = 16, n = 400, s = \frac{16}{\sqrt{400}} = 0.8

Find the probability that the mean age of the individuals sampled is within one year of the mean age for all individuals in the city.​

Using \mu = 30, this is the pvalue of Z when X = 31 subtracted by the pvalue of Z when X = 29. So

X = 31

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

By the Central Limit Theorem

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

Z = \frac{31 - 30}{0.8}

Z = 1.25

Z = 1.25 has a pvalue of 0.8944

X = 29

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

Z = \frac{29 - 30}{0.8}

Z = -1.25

Z = -1.25 has a pvalue of 0.1056

0.8944 - 0.1056 = 0.7888

Rounded to three decimal places, 0.789

The probability is 0.789

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3 years ago
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