Final Answer:
The probability that the mean salary of a sample of 44 specialists is less than $59,500 is approximately 0.0146.
Step-by-step explanation:
Using the z-score formula with the given information:
![\[ z = \frac{{\bar{x} - \mu}}{{\frac{\sigma}{{√(n)}}}} = \frac{{59500 - 59507}}{{\frac{6100}{{√(44)}}}} \]](https://img.qammunity.org/2024/formulas/mathematics/high-school/kpun4fx7fkrmstp9tri5z5tgoopkrmzev3.png)
Calculating this results in a z-score of approximately -0.1717.
Next, referring to a standard normal distribution table or using technology like a statistical calculator or software, the probability corresponding to this z-score can be found. Using technology such as Python or R, one can employ functions like `pnorm` or `scipy.stats.norm.cdf` to find this probability directly from the z-score.
The probability, rounded to four decimal places, is approximately 0.0146, or 1.46%.
This means that in a normally distributed population with a mean of $59,507 and a standard deviation of $6,100, the probability of obtaining a sample mean salary of less than $59,500 from a sample of 44 specialists is about 1.46%. Therefore, it's within the range of expected variations and is not an unusually rare event. In practical terms, this suggests that observing a sample mean salary below $59,500 for a group of 44 specialists is not exceptionally uncommon, given the parameters of the population's distribution.