Respuesta :
Answer:
84.13% of of salaries that are at least $74,000
Step-by-step explanation:
Problems of normally distributed(bell-shaped) samples can be solved using the z-score formula.
In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the zscore 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 pvalue, we get the probability that the value of the measure is greater than X.
In this problem, we have that:
[tex]\mu = 80000, \sigma = 6000[/tex]
What can be said about the percentage of salaries that are at least $74,000?
[tex]Z = \frac{X - \mu}{\sigma}[/tex]
[tex]Z = \frac{74000 - 80000}{6000}[/tex]
[tex]Z = -1[/tex]
[tex]Z = -1[/tex] has a pvalue of 0.1587.
1 - 0.1587 = 0.8413
84.13% of of salaries that are at least $74,000
Answer:
84.13% of salaries are at least $74,000.
Step-by-step explanation:
We are given that Professors at a local university earn an average salary of $80,000 with a standard deviation of $6,000. The salary distribution is approximately bell-shaped.
Let X = Percentage of Salary
So, X ~ N([tex]\mu=80000,\sigma^{2}=6000^{2})[/tex])
Now, the z score probability distribution is given by;
Z = [tex]\frac{X-\mu}{\sigma}[/tex] ~ N(0,1)
where, [tex]\mu[/tex] = population mean
[tex]\sigma[/tex] = standard deviation
So, Percentage of salaries that are at least $74,000 is given by = P(X [tex]\geq[/tex] $74,000)
P(X [tex]\geq[/tex] 74,000) = P( [tex]\frac{X-\mu}{\sigma}[/tex] [tex]\geq[/tex] [tex]\frac{74,000-80,000}{6,000}[/tex] ) = P(Z [tex]\geq[/tex] -1) = P(Z [tex]\leq[/tex] 1)
= 0.84134 {using z table}
Therefore, 84.13% of salaries that are at least $74,000.