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Consider the following probability distribution:

a. Findμ.

b. For a random sample of n = 3 observations from this distribution, find the sampling distribution of the sample mean.

c. Find the sampling distribution of the median of a sample of n = 3 observations from this population.

d. Refer to parts b and c, and show that both the mean and median are unbiased estimators ofμfor this population.

e. Find the variances of the sampling distributions of the sample mean and the sample median.

f. Which estimator would you use to estimateμ? Why?

Short Answer

Expert verified

a)μ=1

b) 1

c) 1

d) Both the mean and median are unbiased

e) Variance of mean=0.214

Variance of median=0.67

f) Mean is a better estimator

Step by step solution

01

Calculation of the meanμ

a.

The calculation of the meanμin the case of the three values of x is shown below:

μ=xp(x)=013+113+213=0+13+23=33=1

Therefore the value ofμis 1.

02

Computation of the sample distribution of the mean

b.

The calculation of the probabilities of the means considering the three values of x is shown below:

Therefore, the sample distribution of the means on adding the probabilities will give 1.

03

Computation of the sample distribution of the median

b.

The list of medians along with the associated probabilities is shown below:

Therefore, the sample distribution of the medians on adding the probabilities will give 1.

04

Determining the unbiasedness of the mean and the median

c.

To check unbiasness of mean and median, following tables are required.

On adding the above probabilities, the final value will be 1 and so the mean will be an unbiased estimator of the μ.

On adding the above probabilities, the final value will be 1 and so the median will be an unbiased estimator of the .

05

Computation of the variances of means and medians

d.

The average of the means can be found and it is subtracted from the respective value of the means. It is then squared and the last column shows the respective probabilities.

The variance is then calculated by multiplying the respective values of by the respective probabilities.

variance=1×0+0.44×0.3327+0.11×0.6727+0.44×0.3327+0.11×0.6727+0.11×0.6727+0.11×1.3327+0××1.3327+0.11×0.6727+0.11×1.3327+0.11×0.6727+0.11×0.3327+0.44×0+0.44×1.3327+1×227+0.11×1.3327+0.44×1.6727+0.11×1.3327+0.44×1.6727+0.11×1.6727+0.11×1.3327+0×127+0×127+0×127+0×127+0×127+0×127=1270.1452+0.0737+0.1452+0.0737+0.0737+0.1463+0+0.0737+0.1463+0.0737+0.1463+0+0.5852+2+0.1463+0.7348+0.1463+0.7348+0.1837+0.1463+0+0+0+0+0+0=5.775227=0.214

The average of the medians has been found and it has been subtracted from the respective value of the medians. It has then squared and the third column shows the respective probabilities.

The variance is then calculated by multiplying the respective values of mean-meanofmedian2by the respective probabilities.

variance=1×0+1×127+1×127+1×127+1×127+0×027+1×127+0×027+0×027+0×027+0×027+0×027+1×227+1×227+1×227+1×227+1×227+1×227+1+×0+1×127+0×127+0×127+0×127+0×127+0×127+0×127+0×127=1270+1+1+1+1+0+1+0+0+0+0+0+2+2+2+2+2+2+0+1+0+0+0+0+0+0+0=1827=0.67

06

Determining the better estimator

e.

It has been observed from the above calculations that the variance of the means is greater than that of the medians.Therefore, it can be envisaged that the median is the better estimator.

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Voltage sags and swells. Refer to the Electrical Engineering (Vol. 95, 2013) study of the power quality (sags and swells) of a transformer, Exercise 2.76 (p. 110). For transformers built for heavy industry, the distribution of the number of sags per week has a mean of 353 with a standard deviation of 30. Of interest is , that the sample means the number of sags per week for a random sample of 45 transformers.

a. FindEχ¯ and interpret its value.

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Refer to Exercise 5.5, in which we found the sampling distribution of the sample median. Is the median an unbiased estimator of the population mean m?

Length of job tenure. Researchers at the Terry College ofBusiness at the University of Georgia sampled 344 business students and asked them this question: “Over the course of your lifetime, what is the maximum number of years you expect to work for any one employer?” The sample resulted in x= 19.1 years. Assume that the sample of students was randomly selected from the 6,000 undergraduate students atthe Terry College and that = 6 years.

  1. Describe the sampling distribution of X¯.
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Question:A random sample of 40 observations is to be drawn from a large population of measurements. It is known that 30% of the measurements in the population are 1s, 20% are 2s, 20% are 3s, and 30% are 4s.

a. Give the mean and standard deviation of the (repeated) sampling distribution ofx¯, the sample mean of the 40 observations.

b. Describe the shape of the sampling distribution ofx¯. Does youranswer depend on the sample size?

Consider the following probability distribution:

  1. Findandσ2.
  2. Find the sampling distribution of the sample mean x for a random sample of n = 2 measurements from this distribution
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  4. Find the sampling distribution of the sample variances2for a random sample of n = 2 measurements from this distribution.
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