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Chapter 8: Q 32. (page 522)

Whelks and mussels The small round holes you often see in seashells were drilled by other sea creatures, who ate the former dwellers of the shells. Whelks often drill into mussels, but this behavior appears to be more or less common in different locations. Researchers collected whelk eggs from the coast of Oregon, raised the whelks in the laboratory, then put each whelk in a container with some delicious mussels. Only9 of 98 whelks drilled into a mussel.

Short Answer

Expert verified

The conditions which are not satisfied are random sample and large count.

Step by step solution

01

Given Information

It is given that n=98

The population is of all whelks.

02

Explanation

  • Selection of whelk eggs is done from coast of Oregon. Hence, whelk does not represent all whelk eggs which is not random sample. Condition of random sample is not met.
  • 98whelks is less than10% of all the whelks. Condition is satisfied.
  • Number of success is 9<10and failures are 98-9=89≥10. Hence condition success and failure should be ≥10is not satisfied.

Therefore, condition for confidence interval is not met.

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Most popular questions from this chapter

Losing weight Refer to Exercise 6.

a. Explain what would happen to the length of the interval if the confidence level was decreased to 90%.

b. How would a 95%confidence interval based on triple the sample size compare to the original 95%interval?

c. As Gallup indicates, the 3percentage point margin of error for this poll includes only sampling variability (what they call “sampling error”). What other potential sources of error (Gallup calls these “non sampling errors”) could affect the accuracy of the 95% confidence interval?

Running red lights A random digit dialing telephone survey of 880 drivers asked, “Recalling the last ten traffic lights you drove through, how many of them were red when you entered the intersections?” Of the 880 respondents, 171 admitted that at least one light had been red.37

a. Construct and interpret a 95% confidence interval for the population proportion.

b. Nonresponse is a practical problem for this survey—only 21.6% of calls that reached a live person were completed. Another practical problem is that people may not give truthful answers. What is the likely direction of the bias: Do you think more or fewer than 171 of the 880 respondents really ran a red light? Why? Are these sources of bias included in the margin of error?

Power lines and cancer Does living near power lines cause leukemia in

children? The National Cancer Institute spent 5years and $5million gathering data on this question. The researchers compared 638children who had leukemia with 620who did not. They went into the homes and measured the magnetic fields in children’s bedrooms, in other rooms, and at the front door. They recorded facts about power lines near the family home and also near the mother’s residence when she was pregnant. Result: No association between leukemia and exposure to magnetic fields of the kind produced by power lines was found.

a. Was this an observational study or an experiment? Justify your answer.

b. Does this study prove that living near power lines doesn’t cause cancer? Explain your answer.

Lying online Many teens have posted profiles on sites such as Facebook. A sample survey asked random samples of teens with online profiles if they included false information in their profiles. Of 170younger teens (ages role="math" localid="1654194610029" 12to14) polled, 117said “Yes.” Of 317older teens (ages 15to17) polled, 152said “Yes.” A 95%confidence interval for pY-pO=the true difference in the proportions of younger teens and older teens who include false information in their profile is 0.120to 0.297.

a. Interpret the confidence interval.

b. Does the confidence interval give convincing evidence of a difference in the true

proportions of younger and older teens who include false information in their profiles?

Explain your answer.

It’s critical Find the appropriate critical value for constructing a confidence interval in each of the following settings.

a. Estimating a population proportion p at a 94% confidence level based on an SRS of size 125

b. Estimating a population mean μ at a 99% confidence level based on an SRS of size 58
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