None of these are correct
In order to expand employment opportunities for traditionally disadvantaged groups, the federal government requires agencies and businesses that receive federal funds or contracts to <u>establish policies aimed at ensuring that all job applicants are treated fairly</u>
This is further explained below.
<h3>What is
employment?</h3>
Generally, An employment contract is an agreement between an employer and an employee that specifies the employee's duties and responsibilities in relation to the employment.
In exchange for their services, the employee receives either a salary or an hourly rate.
In conclusion, In order to increase employment opportunities for demographics that have historically been underrepresented in the workforce, the federal government mandates that organizations and businesses that are recipients of federal funds or contracts develop employment practices that ensure applicants for all jobs are given equal consideration.
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Answer:
Explanation:
Your question has one part only: <em>a) The average weight of the eggs produced by the young hens is 50.1 grams, and only 25% of their eggs exceed the desired minimum weight. If a Normal model is appropriate, what would the standard deviation of the egg weights be?</em>
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<h2><em>Solution</em></h2><h2><em /></h2>
You are given the <em>mean</em>, the reference value, and the <em>percent of egss that exceeds that minimum</em>.
In terms of the parameters of a normal distribution that is:
- <em>mean</em> =<em> 50.1g</em> (μ)
- Area of the graph above X = 51 g = <em>25%</em>
Using a standard<em> normal distribution</em> table, you can find the Z-score for which the area under the curve is greater than 25%, i.e. 0.25
The tables with two decimals for the Z-score show probability 0.2514 for Z-score of 0.67 and probabilidad 0.2483 for Z-score = 0.68.
Thus, you must interpolate. Since, (0.2514 + 0.2483)/2 ≈ 0.25, your Z-score is in the middle.
That is, Z-score = (0.67 + 0.68)/2 = 0.675.
Now use the formula for Z-score and solve for the <em>standard deviation</em> (σ):
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