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A statistic is said to be an unbiased estimator of a parameter if the mean of all its possible values equals the parameter; otherwise, it is said to be a biased estimator. An unbiased estimator yields, on average, the correct value of the parameter, whereas a biased estimator does not.

Part (a): Is the sample mean an unbiased estimator of the population mean? Explain your answer.

Part (b): Is the sample median an unbiased estimator of the population mean? Explain your answer.

Short Answer

Expert verified

Part (a): Yes, as mean of all possible sample means for a fixed sample size is equal to the population mean.

Part (b): Yes, sample median is an biased estimator of population median.

Mean of all possible sample median for sample size n, is not equal to the population median.

Step by step solution

01

Part (a) Step 1. Explain the answer.

Yes, sample mean is an unbiased estimator of the population mean. Since, mean of all possible sample means for a fixed sample size is equal to the population mean.

02

Part (b) Step 1. Explain the answer.

No, sample median is not an unbiased estimator of the population median.

Suppose the population consists of five players says A, B, C, D, Eand the variable under consideration is height of players in inches.

The table shows the height of the players,

Here, the total number of popuation observation is N=5, which is odd. The observations are in increasing order.

So, the population meanrole="math" localid="1652638307953" =N+12th observation

=5+12thobservation=3rdobservation=79

Therefore, the population mean is79inches.

03

Part (b) Step 2. Make a table considering samples of size 3 from the population.

Consider samples of size 3 from the population,


Number of possible samples of size 3 from the population of size 5 is 10.Then,

=78+78+78+79+79+81+79+79+81+8110=79310=79.3

Therefore, mean of all possible sample median for sample size 3, is not equal to the population median 79 inches. Thus, sample median is an biased estimator of population median.

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Most popular questions from this chapter

Suppose that a sample is to be taken without replacement from a finite population of size Nif the sample size is the same as the population size

(a) How many possible samples are there?

(b) What are the possible sample means?

(c) What is the relationship between the only possible sample and the population

Refer to Fig. 7.6on page 306 .

a. Why are the four graphs in Fig. 7.6(a) all centered at the same place?

b. Why does the spread of the graphs diminish with increasing sample size? How does this result affect the sampling error when you estimate a population mean, ฮผby a sample mean, x~ ?

c. Why are the graphs in Fig. 7.6(a) bell shaped?

d. Why do the graphs in Figs. 7.6(b)and (c) become bell shaped as the sample size increases?

The winner of the 2012-2013 National Basketball Association (NBA) championship was the Miami Heat. One possible starting lineup for that team is as follows.

a. Determine the population mean height, ฮผ, of the five players:

b. Consider samples of size 2without replacement. Use your answer to Exercise 7.11(b)on page 295and Definition 3.11on page 140to find the mean, ฮผr, of the variable x^.

c. Find ฮผx*using only the result of part (a).

Why is obtaining the mean and standard deviation of xยฏ a first step in approximating the sample distribution of the sample mean by a normal distribution?

Population data: 1,2,3

Part (a): Find the mean, ฮผ,of the variable.

Part (b): For each of the possible sample sizes, construct a table similar to Table 7.2on the page 293and draw a dotplot for the sampling for the sampling distribution of the sample mean similar to Fig 7.1on page 293.

Part (c): Construct a graph similar to Fig 7.3and interpret your results.

Part (d): For each of the possible sample sizes, find the probability that the sample mean will equal the population mean.

Part (e): For each of the possible sample sizes, find the probability that the sampling error made in estimating the population mean by the sample mean will be 0.5or less, that is, that the absolute value of the difference between the sample mean and the population mean is at most 0.5.

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