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Refer to Exercise 5.18. Find the probability that

  1. x¯is less than 16.
  2. x¯is greater than 23.
  3. x¯is greater than 25.
  4. x¯falls between 16 and 22.
  5. x¯ is less than 14.

Short Answer

Expert verified

a. Probability that x¯is less than 16 is 0.0228.

b. Probability that x¯is greater than 23 is 0.0668.

c. Probability that x¯is greater than 15 is 0.0062.

d. Probability that x¯falls between 16 and 22 is 0.8185.

e. Probability that x¯is less than 14 is 0.00135.

Step by step solution

01

Given information

A random sample of n=64observations is drawn from a population with μ=20and σ=16.

02

Computing the probability that x¯ is less than 16

a.

According to properties of the Sampling distribution of x¯

μx=μand σx¯=σn

Therefore,

μx¯=20and σx¯=1664i.e.σx¯=2

Now,

P(x¯<16)=Px¯-μσln<16-μσln=Px¯-202<16-202=P(z<-2)

Therefore, from z-score table,

P(x¯<16)=0.0228

Thus, probability that x¯is less than 16 is 0.0228.

03

Computing the probability that x¯ is greater than 23 

b.

According to properties of the Sampling distribution of x¯

μx¯=μandσx¯=σn

Therefore,

μx¯=20and σx¯=1664 i.e. σx¯=2

Now,

P(x>23)=Px-μσln>23-μσln=Px-202>23-202=Pz>1.5

Therefore, from z-score table,

P(x>23)=1-Pz<1.5=1-0.9332=0.0668

I

Thus, probability that xis greater than 23 is 0.0668

04

Computing the probability that x is greater than 25

c.

According to properties of the Sampling distribution of x

μx=μand σx=σn

Therefore,

μx=20 and σx=1664 i.e. σx=2

Now,

P(x>25)=Px-μσln>25-μσln=Px-202>25-202=P(z>2.5)

Therefore, from z-score table,

P(x>25)=1-P(z<2.5)=1-0.9937=0.0062

Thus, probability that xis greater than 15 is 0.0062.

05

Computing the probability that x falls between 16 and 22

d.

According to properties of the Sampling distribution of x

μx=μand σx=σn

Therefore,

μx=20 and σx=1664 i.e. σx=2

Now,

P(16<x<22)=P16-μσln<x-μσln<22-μσln=P16-202<x-202<22-202=P-2<z<1

Therefore, from z-score table,

P16<x<22=P-2<z<1=Pz<1-Pz<-2=0.8413-0.02275P(16<x<22)=0.8185

Thus, probability that xfalls between 16 and 22 is 0.8185.

06

Computing the probability that isxless than 14

e.

According to properties of the Sampling distribution of x

μx=μand σxσn

Therefore,

μx=20and σx=1664i.e. σx=2

Now,

Px<14=Px-μσln<14-μσln=Px-202<14-202=P(z<-3)

Therefore, from z-score table,

P(x<14)=P(z<-3)=0.00135

Thus, probability that xis less than 14 is 0.00135.

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Most popular questions from this chapter

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¯.
  2. If the mean for the 6,000 undergraduate students isμ= 18.5 years, findPx¯>19.1.
  3. If the mean for the 6,000 undergraduate students isμ= 19.5 years, findPx¯>19.1.
  4. If,P(x¯>19.1)=0.5 what isμ?
  5. If,Px¯>19.1=0.2 isμgreater than or less than 19.1years? Explain.

Fecal pollution at Huntington Beach. California mandates fecal indicator bacteria monitoring at all public beaches. When the concentration of fecal bacteria in the water exceeds a certain limit (400 colony-forming units of fecal coliform per 100 millilitres), local health officials must post a sign (called surf zone posting) warning beachgoers of potential health risks. For fecal bacteria, the state uses a single-sample standard; if the fecal limit is exceeded in a single sample of water, surf zone posting is mandatory. This single-sample standard policy has led to a recent rash of beach closures in California. A study of the surf water quality at Huntington Beach in California was published in Environmental Science & Technology (September 2004). The researchers found that beach closings were occurring despite low pollution levels in some instances, while in others, signs were not posted when the fecal limit was exceeded. They attributed these "surf zone posting errors" to the variable nature of water quality in the surf zone (for example, fecal bacteria concentration tends to be higher during ebb tide and at night) and the inherent time delay between when a water sample is collected and when a sign is posted or removed. To prevent posting errors, the researchers recommend using an averaging method rather than a single sample to determine unsafe water quality. (For example, one simple averaging method is to take a random sample of multiple water specimens and compare the average fecal bacteria level of the sample with the limit of 400 CFU/100 mL to determine whether the water is safe.) Discuss the pros and cons of using the single sample standard versus the averaging method. Part of your discussion should address the probability of posting a sign when the water is safe and the probability of posting a sign when the water is unsafe. (Assume that the fecal bacteria concentrations of water specimens at Huntington Beach follow an approximately normal distribution.

Will the sampling distribution of x¯always be approximately normally distributed? Explain

Refer to Exercise 5.3.

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

Suppose a random sample of n measurements is selected from a binomial population with the probability of success p = .2. For each of the following values of n, give the mean and standard deviation of the sampling distribution of the sample proportion,

  1. n = 50
  2. n = 1,000
  3. n = 400
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