/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Q12E Question: Refer to Exercise 5.3.... [FREE SOLUTION] | 91Ó°ÊÓ

91Ó°ÊÓ

Question: Refer to Exercise 5.3.

  1. Show thatxis an unbiased estimator ofμ.
  2. Findσx2.
  3. Find the x probability that x will fall within2σxofμ.

Short Answer

Expert verified

a) Proved that xis an unbiased estimator of μ

b) 0.805

c) 0.95

Step by step solution

01

List of probabilities

The list of the probabilities found in Exercise 3 corresponding to the respective means 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

02

Calculation of the mean μ

The calculation of the meanandis shown below:

μx=xp(x)=1(0.2)+2(0.3)+3(0.2)+4(0.2)+5(0.1)=(0.2+0.6+0.6+0.8+0.5)=2.7

E(x)=Exp(x)=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)=0.04+0.18+0.34+0.5+0.6+0.49+0.32+0.18+0.05=2.7

Therefore as the value of localid="1661429696077" role="math" μand localid="1661429661874" E(x)are 2.7, localid="1661429676073" xis an unbiased estimator of localid="1661429690114" μ.

03

Calculation of the variance σx2

b.

The calculation of the varianceσx2is shown below:

σx2=∑(mean-x)2p(x)=1-2.72(0.04)+1.5-2.720.12+2-2.720.17+2.5-2.720.20+3-2.720.20+3.5-2.72(0.14)+4-2.720.08+4.5-2.720.04+5-2.720.01=(0.1156+0.1728+0.0833+0.008+0.018+0.0896+0.1352+0.1296+0.0529)=0.805

04

Calculation of the probability

In order to find out the probability, the2σxhas to be calculated whereσxis the standard deviation. So,

σx=σx2=0.805=0.8972σx=2×0.897=1.794

Now the range is calculated below:

2σx+x=1.794+2.7=4.494x-2σx=2.7-1.794=0.906

Therefore the probability thatxwill stay within the range (0.906, 4.494) is shown below:

probability=p(1)+p(1.5)+p(2)+p(2.5)+p(3)+p(3.5)+p(4)+p(4.5)=0.04+0.12+0.17+0.20+0.20+0.14+0.08=0.95

Therefore the probability thatlocalid="1661429738495" xwill stay within the range (0.906, 4.494) is 0.95

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91Ó°ÊÓ!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Question: Consider the following probability distribution:


a. Findμand σ2.

b. Find the sampling distribution of the sample mean x for a random sample of n = 2 measurements from this distribution

c. Show thatxis an unbiased estimator of μ. [Hint: Show that∑(x)=∑xp(x)=μ. ]

d. Find the sampling distribution of the sample variances2for a random sample of n = 2 measurements from this distribution.

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

σX¯=σn

  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

σA=σn3

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

  1. Suppose that the population standard deviation σis equal to 10 and that the sample size is 64. Calculate the standard errors of x¯and 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¯?

Suppose xequals the number of heads observed when asingle coin is tossed; that is, x= 0 or x= 1. The population corresponding to xis the set of 0s and 1s generated when thecoin is tossed repeatedly a large number of times. Supposewe select n= 2 observations from this population. (That is,we toss the coin twice and observe two values of x.)

  1. List the three different samples (combinations of 0s and1s) that could be obtained.
  2. Calculate the value of X¯ffor each of the samples.
  3. Show that the sample proportion of 1s, p^, is equal to X¯.
  4. List the values thatp^can assume, and find the probabilitiesof observing these values.
  5. Construct a graph of the sampling distribution ofp^.

Errors in filling prescriptions A large number of preventable errors (e.g., overdoses, botched operations, misdiagnoses) are being made by doctors and nurses in U.S. hospitals. A study of a major metropolitan hospital revealed that of every 100 medications prescribed or dispensed, 1 was in error,

but only 1 in 500 resulted in an error that caused significant problems for the patient. It is known that the hospital prescribes and dispenses 60,000 medications per year.

  1. What is the expected proportion of errors per year at this hospital? The expected proportion of significant errors per year?
  2. Within what limits would you expect the proportion significant errors per year to fall?

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?

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.