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Whelks and mussels The small round holes you often see in sea shells 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. Only 9of98whelks drilled into a mussel. The researchers want to estimate the proportion p of Oregon whelks that will spontaneously drill into mussels.

Short Answer

Expert verified

All three conditions for confidence interval is not satisfied.

Step by step solution

01

Step-1 Given Information 

Given in the question that ,

Number of success=9The researchers want to estimate the proportion pof Oregon whelks that will spontaneously drill into mussels.

02

Step-2 Explanation

To calculate a confidence interval three conditions should be satisfied. The conditions are Random, Independent and Normal.

The condition of random is unknown in the description. Thus, random is not satisfied.

Since the sample size is less than 10%of the population size thus the condition of independent is satisfied.

The survey results the number of success is 9is less than 10thus condition of normal is not satisfied.

Hence, all three conditions for confidence interval is not satisfied.

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Most popular questions from this chapter

98% Confidence find z*for a98%confidence interval using table A or tour calculator. show your method.

Scientists collect data on the blood cholesterol levels (milligrams per deciliter of blood) of a random sample of 24laboratory rats. A 95%confidence interval for the mean blood cholesterol level Mis 80.2to 89.8. Which of the following would cause the most worry about the validity of this interval?

(a) There is a clear outlier in the data.

(b) A stemplot of the data shows a mild right skew.

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(e) None of these would be a problem because the t procedures are robust.

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(a) Construct a plot that displays the distribution of the number of accidents effectively.
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