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Consider the population described by the probability distribution shown below.

The random variable x is observed twice. If these observations are independent, verify that the different samples of size 2 and their probabilities are as shown below.

a. Find the sampling distribution of the sample meanx.

b. Construct a probability histogram for the sampling distribution ofx.

c. What is the probability thatxis 4.5 or larger?

d. Would you expect to observe a value ofxequal to 4.5 or larger? Explain.

Short Answer

Expert verified

a.

Mean

Probability

1

0.04

1.5

0.12

2

0.17

2.5

0.20

3

0.20

3.5

0.14

4

0.08

4.5

0.04

5

0.01

b.

c. The required answer is 0.05.

d. The value ofxisequal to 4.5.

Step by step solution

01

Calculation of the value of the mean

a.

The meanof the respective samples has been calculated by summing up the numbers and then dividing the same by 2.The final values are shown below.

Sample

Mean

1,1

1

1,2

1.5

1,3

2

1,4

2.5

1,5

3

2,1

1.5

2,2

2

2,3

2.5

2,4

3

2,5

3.5

3,1

2

3,2

2.5

3,3

3

3,4

3.5

3,5

4

4,1

2.5

4,2

3

4,3

3.5

4,4

4

4,5

4.5

5,1

3

5,2

3.5

5,3

4

5,4

4.5

5,5

5

02

Calculation of the probabilities

The respective probabilities of the samples are added to get the final probabilities of the mean values, as shown below.

Mean

Probability

1

0.04

1.5

0.06+0.06=0.12

2

0.04+0.09+0.04=0.17

2.5

0.04+0.06+0.06+0.04=0.20

3

0.02+0.06+0.06+0.04=0.20

3.5

0.03+0.04+0.04+0.06+0.02=0.20

4

0.02+0.04+0.04+0.03=0.14

4.5

0.02+0.02=0.04

5

0.01

The probabilities of the respective samples are greater than 0 but less than 1.

03

List of the probabilities of the values of the means

b.

The means of the respective samples have been calculated by summing up the numbers and then dividing the same by 2.The final values are shown below.

Mean

Probability

1

0.04

1.5

0.12

2

0.17

2.5

0.20

3

0.20

3.5

0.14

4

0.08

4.5

0.04

5

0.01

04

Elucidation of the graph

The graph contains probabilities on the y-axis and the values of the means of x from 1 to 5 on the x-axis.

From the graph, it can be deduced that 2.5 and 3 show the highest probability, which is 0.20.

05

List of the probabilities of the values of the means

c.

The list of all the probabilities of the mean values is shown below.

Mean

Probability

1

0.04

1.5

0.12

2

0.17

2.5

0.20

3

0.20

3.5

0.14

4

0.08

4.5

0.04

5

0.01

06

Computation of the probabilities

The calculation of the probability of xto be 4.5 and above is shown below.

localid="1658118837019" P(x4.5)=P(x=5)=0.04+0.01=0.5

The final value of the probability ofxto be 4.5 and above is 0.05.

07

Determination of the probabilities of the means 

d.

From Part (a), it has been found that the probability of x is 0.04 when it is equal to 4.5, and when it is above 4.5, the probability is 0.01. Therefore, the probability of being equal to 4.5 is larger than that ofxbeinglarger than 4.5.

08

Reason for x being equal to 4.5

It has been observed that in Part (a),x has only one value, that is, 5 (above 4.5). On the other hand, in the table, 4.5 has appeared two times.So, it can be deduced thatx being equal to 4.5 has a greater chance.

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Most popular questions from this chapter

The probability distribution shown here describes a population of measurements that can assume values of 0, 2, 4, and 6, each of which occurs with the same relative frequency:

  1. List all the different samples of n = 2 measurements that can be selected from this population. For example, (0, 6) is one possible pair of measurements; (2, 2) is another possible pair.
  2. Calculate the mean of each different sample listed in part a.
  3. If a sample of n = 2 measurements is randomly selected from the population, what is the probability that a specific sample will be selected.
  4. Assume that a random sample of n = 2 measurements is selected from the population. List the different values of x found in part b and find the probability of each. Then give the sampling distribution of the sample mean x in tabular form.
  5. Construct a probability histogram for the sampling distribution ofx.

A random sample of n= 300 observations is selectedfrom a binomial population with p= .8. Approximateeach of the following probabilities:

  1. Pp^<0.83
  2. Pp^>0.75
  3. P0.79<p^<0.81

Rental car fleet evaluation. National Car Rental Systems, Inc., commissioned the U.S. Automobile Club (USAC) to conduct a survey of the general condition of the cars rented to the public by Hertz, Avis, National, and Budget Rent-a-Car.* USAC officials evaluate each company鈥檚 cars using a demerit point system. Each car starts with a perfect score of 0 points and incurs demerit points for each discrepancy noted by the inspectors. One measure of the overall condition of a company鈥檚 cars is the mean of all scores received by the company (i.e., the company鈥檚 fleet mean score). To estimate the fleet mean score of each rental car company, 10 major airports were randomly selected, and 10 cars from each company were randomly rented for inspection from each airport by USAC officials (i.e., a sample of size n = 100 cars from each company鈥檚 fleet was drawn and inspected).

a. Describe the sampling distribution of x, the mean score of a sample of n = 100 rental cars.

b. Interpret the mean of x in the context of this problem.

c. Assume=30 and =60for one rental car company. For this company, findPx45 .

d. Refer to part c. The company claims that their true fleet mean score 鈥渃ouldn鈥檛 possibly be as high as 30.鈥 The sample mean score tabulated by USAC for this company was 45. Does this result tend to support or refute the claim? Explain.

Question: The standard deviation (or, as it is usually called, the standard error) of the sampling distribution for the sample mean, x , is equal to the standard deviation of the population from which the sample was selected, divided by the square root of the sample size. That is

X=n

  1. As the sample size is increased, what happens to the standard error of? Why is this property considered important?
  2. Suppose a sample statistic has a standard error that is not a function of the sample size. In other words, the standard error remains constant as n changes. What would this imply about the statistic as an estimator of a population parameter?
  3. Suppose another unbiased estimator (call it A) of the population mean is a sample statistic with a standard error equal to

A=n3

Which of the sample statistics,xor A, is preferable as an estimator of the population mean? Why?

  1. Suppose that the population standard deviation is equal to 10 and that the sample size is 64. Calculate the standard errors of xand A. Assuming that the sampling distribution of A is approximately normal, interpret the standard errors. Why is the assumption of (approximate) normality unnecessary for the sampling distribution ofx?

Use the computer to generate 500 samples, each containing n = 25 measurements, from a population that contains values of x equal to 1, 2, . . 48, 49, 50 Assume that these values of x are equally likely. Calculate the sample mean () and median m for each sample. Construct relative frequency histograms for the 500 values of ()and the 500 values of m. Use these approximations to the sampling distributions of ()and m to answer the following questions:

a. Does it appear that and m are unbiased estimators of the population mean? [Note:=25.5]

b. Which sampling distribution displays greater variation?

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