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grin007 [14]
3 years ago
10

A job has a normal time of 12 minutes, a performance rating of 0.80, and an allowance of 20 percent of job time. The standard ti

me for this job in minutes is:_______
a. 11.52.
b. 12.
c. 14.4.
d. 15.
e. depends on the number of cycles observed.
Mathematics
1 answer:
sleet_krkn [62]3 years ago
3 0

Solution :

The standard time for doing a job in minutes is given by :

Standard time = Normal time + normal time x allowance factor.

Here, it is given that ,

Allowance factor = 20%

                            = 0.20

Normal time of doing a a job = 12 minutes.

Therefore,

Standard time = Normal time + normal time x allowance factor

Standard time = 12 + 12 x 0.20

                        = 12 + 2.4

                        = 14.4

Thus, the standard time for doing the job is 14.4 minutes.

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A population has a mean of 200 and a standard deviation of 50. Suppose a sample of size 100 is selected and x is used to estimat
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Answer:

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b) 0.9544 = 95.44% probability that the sample mean will be within +/- 10 of the population mean.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

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.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

In this question, we have that:

\mu = 200, \sigma = 50, n = 100, s = \frac{50}{\sqrt{100}} = 5

a. What is the probability that the sample mean will be within +/- 5 of the population mean (to 4 decimals)?

This is the pvalue of Z when X = 200 + 5 = 205 subtracted by the pvalue of Z when X = 200 - 5 = 195.

Due to the Central Limit Theorem, Z is:

Z = \frac{X - \mu}{s}

X = 205

Z = \frac{X - \mu}{s}

Z = \frac{205 - 200}{5}

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Z = 1 has a pvalue of 0.8413.

X = 195

Z = \frac{X - \mu}{s}

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Z = -1 has a pvalue of 0.1587.

0.8413 - 0.1587 = 0.6426

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b. What is the probability that the sample mean will be within +/- 10 of the population mean (to 4 decimals)?

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Z = \frac{210 - 200}{5}

Z = 2

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Z = \frac{X - \mu}{s}

Z = \frac{190 - 200}{5}

Z = -2

Z = -2 has a pvalue of 0.0228.

0.9772 - 0.0228 = 0.9544

0.9544 = 95.44% probability that the sample mean will be within +/- 10 of the population mean.

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