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Sagot :
Answer:
The upper 20% of the weighs are weights of at least X, which is [tex]X = 0.84\sigma + \mu[/tex], in which [tex]\sigma[/tex] is the standard deviation of all weights and [tex]\mu[/tex] is the mean.
Step-by-step explanation:
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.
Upper 20% of weights:
The upper 20% of the weighs are weighs of at least X, which is found when Z has a p-value of 0.8. So X when Z = 0.84. Then
[tex]Z = \frac{X - \mu}{\sigma}[/tex]
[tex]0.84 = \frac{X - \mu}{\sigma}[/tex]
[tex]X = 0.84\sigma + \mu[/tex]
The upper 20% of the weighs are weights of at least X, which is [tex]X = 0.84\sigma + \mu[/tex], in which [tex]\sigma[/tex] is the standard deviation of all weights and [tex]\mu[/tex] is the mean.
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