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k0ka [10]
1 year ago
12

in a study evaluating the relationship between stress and muscle cramps, half the subjects are randomly assigned to be exposed t

o increased stress by being placed into an elevator that falls rapidly and stops abruptly and the other half are left at no or baseline stress.
Mathematics
1 answer:
stiks02 [169]1 year ago
7 0

The study creates stress in a(0ne) way that might affect muscle cramps.

What is muscle cramps ?

  • Overuse of a muscle, dehumidification, muscle strain or simply holding a position for a prolonged period can beget a muscle cramp. In numerous cases, still, the cause is not known.
  • Although utmost muscle cramps are inoffensive, some may be related to an beginning medical condition, similar as shy blood force.
  • Cramps can have causes that are not due to underpinning complaint. exemplifications include dehumidification, emphatic exercise or lack of muscle use. Muscle cramps are unforeseen muscle condensation.
  • Also called muscle spasms or charley nags, a muscle cramp can be a common symptom of numerous effects, like exercise strain or a medical condition. Muscle cramps generally go down without treatment and can be watched for at home.

The study creates stress in a(0ne) way that might affect muscle cramps. If an elevator falls, fleetly and stops suddenly, that could affect muscle cramps more because of the physical action than by the stress it convinced. I don’t suppose this trial would help answer whether there's a unproductive relationship between increases stress and muscle cramps.

Learn more about muscle cramp here:

brainly.com/question/19064082

#SPJ4

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A distribution of values is normal with a mean of 220 and a standard deviation of 13. From this distribution, you are drawing sa
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Answer:

The interval containing the middle-most 48% of sample means is between 218.59 to 221.41.

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 distributied random variable X, with mean \mu and standard deviation \sigma, the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}

In this problem, we have that:

\mu = 220, \sigma = 13, n = 35, s = \frac{13}{\sqrt{35}} = 2.1974

Find the interval containing the middle-most 48% of sample means:

50 - 48/2 = 26th percentile to 50 + 48/2 = 74th percentile. So

74th percentile

value of X when Z has a pvalue of 0.74. So X when Z = 0.643.

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

By the Central Limit Theorem

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

0.643 = \frac{X - 220}{2.1974}

X - 220 = 0.643*2.1974

X = 221.41

26th percentile

Value of X when Z has a pvalue of 0.26. So X when Z = -0.643

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

-0.643 = \frac{X - 220}{2.1974}

X - 220 = -0.643*2.1974

X = 218.59

The interval containing the middle-most 48% of sample means is between 218.59 to 221.41.

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