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nlexa [21]
3 years ago
15

The salary of teachers in a particular school district is normally distributed with a mean of $50,000 and a standard deviation o

f $2,500. Due to budget limitations, it has been decided that the teachers who are in the top 2.5% of the salaries would not get a raise. What is the salary level that divides the teachers into one group that gets a raise and one that doesn't?
A. -1.96
B. 1.96
C. 45,100
D. 54,900
Mathematics
1 answer:
andrey2020 [161]3 years ago
4 0

Answer:

D. 54,900

Step-by-step explanation:

We have been given that the salary of teachers in a particular school district is normally distributed with a mean of $50,000 and a standard deviation of $2,500.

To solve our given problem, we need to find the sample score using z-score formula and normal distribution table.

First of all, we will find z-score corresponding to probability 0.975(1-0.025) using normal distribution table.  

From normal distribution table, we get z-score corresponding is 1.96.

Now, we will use z-score formula to find sample score as:

z=\frac{x-\mu}{\sigma}, where,

z = Z-score,

z = Sample score,

\mu = Mean,

\sigma = Standard deviation

1.96=\frac{x-50,000}{2,500}

1.96*2,500=\frac{x-50,000}{2,500}*2,500

4900=x-50,000

4900+50,000=x-50,000+50,000

54900=x

Therefore, the salary of $54900 divides the teachers into one group that gets a raise and one that doesn't.

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Among cases of heart pacemaker malfunctions, were found to be caused by firmware, which is software programmed into the device.
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Complete question is;

Among 8834 cases of heart pacemaker malfunctions, 504 were found to be caused by firmware, which is software programmed into the device. If the firmware is tested in three different pacemakers randomly selected from this batch of 8834 and the entire batch is accepted if there are no failures, what is the probability that the firmware in the entire batch will be accepted? Is this procedure likely to result in the entire batch being accepted?

Answer:

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Step-by-step explanation:

We are told that out of the 8834 cases of heart pacemaker malfunctions, 504 were found to be caused by firmware.

Thus,

Cases not caused by firmware = 8834 - 504 = 8330

So, probability of the first case not being affected by firmware is;

P(first case not caused by firmware) = 8330/8834

Also,

Probability of second case not being affected by firmware is given as;

P(second case not caused by firmware|first case not affected by firmware) = 8329/8833

Similarly,

Probability of third case not being affected by firmware is given as;

P(third case not caused by firmware|first and second not caused by firmware) = 8328/8832

Now, looking at the 3 Probabilities gotten, it is obvious that the events are not independent because the probability of occurence of one event depends on the probability of occurence of the other event.

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P(A & B) = P(B) × P(A|B)

Thus;

P(All three not caused by firmware) = P(first case not caused by firmware) × P(second case not caused by firmware|first case not affected by firmware) × P(third case not caused by firmware|first and second not caused by firmware)

Plugging in the relevant values, we have;

P(All three not caused by firmware) = (8330/8834) × (8329/8833) × (8328/8832)

P(All three are not caused by firmware) = 0.83840506679 ≈ 83.84%

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