Answer:
(a) The fraction of employees is 0.84.
(b)

(c)

(d) No. The left part of the distribution would be truncated too much.
Step-by-step explanation:
(a) If the weekly salaries are normally distributed, estimate the fraction of employees that make more than $300 per week.
We have to calculate the z-value and compute the probability

(b) If every employee receives a year-end bonus that adds $100 to the paycheck in the final week, how does this change the normal model for that week?
The mean of the salaries grows $100.

The standard deviation stays the same ($450)
![\sigma_{new}=\sqrt{\frac{1}{N} \sum{[(x+C)-(\mu+C)]^2} } =\sqrt{\frac{1}{N} \sum{(x+C-\mu-C)^2} }\\\\ \sigma_{new}=\sqrt{\frac{1}{N} \sum{(x-\mu)^2} } =\sigma](https://tex.z-dn.net/?f=%5Csigma_%7Bnew%7D%3D%5Csqrt%7B%5Cfrac%7B1%7D%7BN%7D%20%5Csum%7B%5B%28x%2BC%29-%28%5Cmu%2BC%29%5D%5E2%7D%20%20%7D%20%3D%5Csqrt%7B%5Cfrac%7B1%7D%7BN%7D%20%5Csum%7B%28x%2BC-%5Cmu-C%29%5E2%7D%20%20%7D%5C%5C%5C%5C%20%5Csigma_%7Bnew%7D%3D%5Csqrt%7B%5Cfrac%7B1%7D%7BN%7D%20%5Csum%7B%28x-%5Cmu%29%5E2%7D%20%20%7D%20%3D%5Csigma)
(c) If every employee receives a 5% salary increase for the next year, how does the normal model change?
The increases means a salary X is multiplied by 1.05 (1.05X)
The mean of the salaries grows 5%, to $787.5.

The standard deviation increases by a 5% ($472.5)
![\sigma_{new}=\sqrt{\frac{1}{N} \sum{[(ax)-(a\mu)]^2} } =\sqrt{\frac{1}{N} \sum{a^2(x-\mu)^2} }\\\\ \sigma_{new}=\sqrt{a^2}\sqrt{\frac{1}{N} \sum{(x-\mu)^2}}=a*\sigma=1.05*450=472.5](https://tex.z-dn.net/?f=%5Csigma_%7Bnew%7D%3D%5Csqrt%7B%5Cfrac%7B1%7D%7BN%7D%20%5Csum%7B%5B%28ax%29-%28a%5Cmu%29%5D%5E2%7D%20%20%7D%20%3D%5Csqrt%7B%5Cfrac%7B1%7D%7BN%7D%20%5Csum%7Ba%5E2%28x-%5Cmu%29%5E2%7D%20%20%7D%5C%5C%5C%5C%20%5Csigma_%7Bnew%7D%3D%5Csqrt%7Ba%5E2%7D%5Csqrt%7B%5Cfrac%7B1%7D%7BN%7D%20%5Csum%7B%28x-%5Cmu%29%5E2%7D%7D%3Da%2A%5Csigma%3D1.05%2A450%3D472.5)
(d) If the lowest salary is $300 and the median salary is $525, does a normal model appear appropriate?
No. The left part of the distribution would be truncated too much.