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Sagot :
Answer:
The probability that the mean from that sample will be between 183 and 186 is 0.0994 = 9.94%.
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 [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the z-score of a measure X is given by:
[tex]Z = \frac{X - \mu}{\sigma}[/tex]
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 estabilishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
A population has a mean of 180 and a standard deviation of 24.
This means that [tex]\mu = 180, \sigma = 24[/tex]
A sample of 100 observations will be taken.
This means that [tex]n = 100, s = \frac{24}{\sqrt{100}} = 2.4[/tex]
The probability that the mean from that sample will be between 183 and 186 is:
This is the pvalue of Z when X = 186 subtracted by the pvalue of Z when X = 183. So
X = 186
[tex]Z = \frac{X - \mu}{\sigma}[/tex]
By the Central Limit Theorem
[tex]Z = \frac{X - \mu}{s}[/tex]
[tex]Z = \frac{186 - 180}{2.4}[/tex]
[tex]Z = 2.5[/tex]
[tex]Z = 2.5[/tex] has a pvalue of 0.9938
X = 183
[tex]Z = \frac{X - \mu}{s}[/tex]
[tex]Z = \frac{183 - 180}{2.4}[/tex]
[tex]Z = 1.25[/tex]
[tex]Z = 1.25[/tex] has a pvalue of 0.8944
0.9938 - 0.8944 = 0.0994
The probability that the mean from that sample will be between 183 and 186 is 0.0994 = 9.94%.
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