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vova2212 [387]
3 years ago
5

To estimate the mean age for a population of 4000 employees, a simple random sample of 40 employees is selected. If the populati

on standard deviation is 8.2 years, computer the standard error of the mean. (Round to one decimal place) What is the probability that the sample mean age of the employees will be within 2 years of the population mean age
Mathematics
1 answer:
harkovskaia [24]3 years ago
6 0

Answer:

The standard error of the mean is 1.3.

87.64% probability that the sample mean age of the employees will be within 2 years of the population mean age

Step-by-step explanation:

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

Normal probability distribution:

Problems of normally distributed samples are solved using 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 random variable X, with mean \mu and standard deviation \sigma, a large sample size can be approximated to a normal distribution with mean \mu and standard deviation, which is also called standard error s = \frac{\sigma}{\sqrt{n}}

In this problem, we have that:

\sigma = 8.2, n = 40

Computer the standard error of the mean

s = \frac{8.2}{\sqrt{40}} = 1.3

The standard error of the mean is 1.3.

What is the probability that the sample mean age of the employees will be within 2 years of the population mean age

This is the pvalue of Z when X = \mu + 2 subtracted by the pvalue of Z when X = \mu - 2. So

X = \mu + 2

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

By the Central Limit Theorem

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

Z = \frac{\mu + 2 - \mu}{1.3}

Z = 1.54

Z = 1.54 has a pvalue of 0.9382

-----

X = \mu - 2

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

Z = \frac{\mu - 2 - \mu}{1.3}

Z = -1.54

Z = -1.54 has a pvalue of 0.0618

0.9382 - 0.0618 = 0.8764

87.64% probability that the sample mean age of the employees will be within 2 years of the population mean age

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Answer:

Mean=13.22

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  • The mean is  a measure of central tendency in a probabilistic sense. Matematically speaking,  it can be calculated as the average of the elements that conform a set of numbers. It is important because it provides you with information about a dataset without having to know every value of your data. As an example, if you have a sample of the age of school teachers, the mean age of teachers will tell you what is the average age among all the teachers in the sample.It can be calculated like this:  \frac{1}{n} \times \sum x = \frac{1}{n} \times (12+12.5+18.2+13.6+15.3+7.7) = 13.22
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  • Standar deviation is a measure of dispersion around the mean value. Its value is an indicator of how near are the observations in the sample, from the mean.  A low standard deviation imply that the observations in your dataset are closed to the mean value. In terms of the teachers’ example, if the mean is 50 and the standard deviation is 2, many of the teachers in your datasets are between 48-52 years old. Following this example, if the standard deviation was 10 and the mean 50, most of the teachers would be between 40 and 60 years old (mean plus and less 10 years). The lowest the standard deviation, the more informative the mean: when the standard deviation is small, the values of the sample are closer to the mean. To obtain the standar deviation value one should use the following equation: s=\sqrt{\frac{1}{n-1} \times \sum{ (x_{i} - \bar{x})^{2} } \\, where \bar{x} is the mean value that you calculated before, and "n" is the number of observations in the sample.

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