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iogann1982 [59]
3 years ago
8

What’s the answer to 14?

Mathematics
1 answer:
vfiekz [6]3 years ago
7 0

Answer:

  • |t -(-5)| = 1.5
  • [-6.5, -3.5] = [minimum, maximum]

Step-by-step explanation:

The magnitude of the difference between the temperature (t) and -5 will be 1.5 at the limits:

  |t -(-5)| = 1.5

This is equivalent to two equations:

  • t +5 = -1.5
  • t +5 = 1.5

In each case, the equation is solved by subtracting 5 from both sides:

  • t = -6.5 . . . . minimum allowed temperature
  • t = -3.5 . . . . maximum allowed temperature
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Step-by-step explanation:

Since Michelle got an average score of 80 on two tests, to determine what score she must get on the third test so that her average score for the three tests is the same as the average score for the first two tests, the following calculation must be performed:

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Suppose that the walking step lengths of adult males are normally distributed with a mean of 2.5 feet and a standard deviation o
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0% probability that the mean of the sample taken is less than 2.2 feet.

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.

In a set with mean \mu and standard deviation \sigma, the z-score 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 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.

Mean of 2.5 feet and a standard deviation of 0.2 feet.

This means that \mu = 2.5, \sigma = 0.2

Sample of 41

This means that n = 41, s = \frac{0.2}{\sqrt{41}}

Find the probability that the mean of the sample taken is less than 2.2 feet.

This is the p-value of Z when X = 2.2 So

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

By the Central Limit Theorem

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

Z = \frac{2.2 - 2.5}{\frac{0.2}{\sqrt{41}}}

Z = -9.6

Z = -9.6 has a p-value of 0.

0% probability that the mean of the sample taken is less than 2.2 feet.

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3 years ago
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