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Salmonella poisoning from eating an ice cream bar.Recently, a case of salmonella (bacterial) poisoning wastraced to a particular brand of ice cream bar, and themanufacturer removed the bars from the market. Despitethis response, many consumers refused to purchase anybrand of ice cream bars for some period of time after the event (McClave, personal consulting). One manufacturerconducted a survey of consumers 6 months after theoutbreak. A sample of 244 ice cream bar consumers wascontacted, and 23 respondents indicated that they wouldnot purchase ice cream bars because of the potential forfood poisoning.

  1. What is the point estimate of the true fraction of the entiremarket who refuse to purchase bars 6 months after the out-break?
  2. Is the sample size large enough to use the normalapproximation for the sampling distribution of the estimator of the binomial probability? Justify your response.
  3. Construct a 95% confidence interval for the true proportionof the market who still refuses to purchase icecream bars 6 months after the event.
  4. Interpret both the point estimate and confidence interval in terms of this application.

Short Answer

Expert verified
  1. The point estimate of the true fraction of the entire market who refuse to purchase bars 6 months after the outbreak is 0.1027.
  2. Yes, the sample size is large enough to use the normal approximation.
  3. The 95% confidence interval is [0.06,0.14].
  4. In terms of this application, the 95% confidence interval is constructed in this way that the interval contains the proportion of the point estimator that is the true fraction of the entire market that refuse to purchase bars 6 months after the outbreak.

Step by step solution

01

Given information

Recently there was traced a poisoning outbreak for a particular ice-cream brand. Then, many consumers refused to buy the other ice-creams even though the poisonous brand is removed from the market.

A survey of customers is taken after 6 months of the event happened by one manufacturer. They took a sample of 244 ice-cream bar consumers and find that 23 consumers still had not purchased any ice-cream bars because of that poisoning incident.

02

Calculate the point estimate

a.

Let’s consider the sample sizen=244 and the number of consumers who have not purchased the ice cream bars, data-custom-editor="chemistry" x=23.

So, the sample proportion, that is the true fraction of the entire market who refuses to purchase bars 6 months after the outbreak is,

p^=xn=23244=0.1027

Thus, the required point estimate is 0.1027.

03

Validate the approximation

b.

Consider,q^ that is the point estimate of those consumers who purchased bars.

q^=1-p^=1-0.1207=0.8973

So, by the normal approximation of the binomial distribution there can be concluded that, if the quantities of np^andnq^are greater than 15 then the normal approximation can be used.

Hence, the sample size is 244, so, np^=25.05andnq^=218.94.

Therefore, the sample size is large enough to use the normal approximation.

04

Construction of 95% confidence interval

c.

The 95% confidence interval for the binomial proportion is defined as,

[p^-Zαp^q^nzp^+Zαp^q^n]

Now, the confidence level is data-custom-editor="chemistry" CL=0.95, then,

α=1-CL=1-0.95=0.05

And α2=0.025.

Therefore, by the standard normal probability table,

Zα2=Z0.025=1.96.

Thus, the interval is,

p^-Z0.025p^q^n,p^+Z0.025p^q^n=0.1027-1.960.1027×0.8973244,0.1027+1.960.1027×0.8973244=0.1027-0.039,0.1027+0.039=0.06,0.14

Therefore, the 95% confidence that approximately between 6% and 14%.

05

Interpretation of the point estimate and confidence interval

d.

In terms of this application, the 95% confidence interval constructed in this way that the interval contains the proportion of the point estimator that is the true fraction of the entire market that refuse to purchase bars 6 months after the outbreak.

The 95% confidence interval is between 6% and 14% and the point estimator is approximately 10%.

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Most popular questions from this chapter

Suppose you wish to estimate a population mean correct to within .20 with probability equal to .90. You do not know σ2, but you know that the observations will range in value between 30 and 34.

a. Find the approximate sample size that will produce the desired accuracy of the estimate. You wish to be conservative to ensure that the sample size will be ample to achieve the desired accuracy of the estimate. [Hint: Using your knowledge of data variation from Section 2.6, assume that the range of the observations will equal 4σ.]

b. Calculate the approximate sample size, making the less conservative assumption that the range of the observations is equal to 6σ.

Unethical corporate conduct. How complicit are entrylevel accountants in carrying out an unethical request from their superiors? This was the question of interest in a study published in the journal Behavioral Research in Accounting (July 2015). A sample of 86 accounting graduate students participated in the study. After asking the subjects to perform what is clearly an unethical task (e.g., to bribe a customer), the researchers measured each subject’s intention to comply with the unethical request score. Scores ranged from -1.5 (intention to resist the unethical request) to 2.5 (intention to comply with the unethical request). Summary statistics on the 86 scores follow: x¯=2.42,s=2.84.

a. Estimate μ, the mean intention to comply score for the population of all entry-level accountants, using a 90% confidence interval.

b. Give a practical interpretation of the interval, part a.

c. Refer to part a. What proportion of all similarly constructed confidence intervals (in repeated sampling) will contain the true value of μ?

d. Compute the interval, x¯±2s. How does the interpretation of this interval differ from that of the confidence interval, part a?

“Out of control” production processes. When companies employ control charts to monitor the quality of their products, a series of small samples is typically used to determine if the process is “in control” during the period of time in which each sample is selected. (We cover quality-control charts in Chapter 13.) Suppose a concrete-block manufacturer samples nine blocks per hour and tests the breaking strength of each. During 1 hour’s test, the mean and standard deviation are 985.6 pounds per square inch (psi) and 22.9 psi, respectively. The process is to be considered “out of control” if the true mean strength differs from 1,000 psi. The manufacturer wants to be reasonably certain that the process is really out of control before shutting down the process and trying to determine the problem. What is your recommendation?

Shopping on Black Friday. The day after Thanksgiving— called Black Friday—is one of the largest shopping days in the United States. Winthrop University researchers conducted interviews with a sample of 38 women shopping on Black Friday to gauge their shopping habits and reported the results in the International Journal of Retail and Distribution Management (Vol. 39, 2011). One question was, “How many hours do you usually spend shopping on Black Friday?” Data for the 38 shoppers are listed in the accompanying table.

a. Describe the population of interest to the researchers.

b. What is the quantitative variable of interest to the researchers?

c. Use the information in the table to estimate the population mean number of hours spent shopping on Black Friday with a 95% confidence interval.

d. Give a practical interpretation of the interval.

e. A retail store advertises that the true mean number of hours spent shopping on Black Friday is 5.5 hours. Can the store be sued for false advertising? Explain.

Scallops, sampling, and the law. Interfaces (March–April 1995) presented the case of a ship that fishes for scallops off the coast of New England. In order to protect baby scallops from being harvested, the U.S. Fisheries and Wildlife Service requires that “the average meat per scallop weigh at least 136 of a pound.” The ship was accused of violating this weight standard. Author Arnold Barnett lays out the scenario:

The vessel arrived at a Massachusetts port with 11,000 bags of scallops, from which the harbormaster randomly selected 18 bags for weighing. From each such bag, his agents took a large scoopful of scallops; then, to estimate the bag’s average meat per scallop, they divided the total weight of meat in the scoopful by the number of scallops it contained. Based on the 18 [numbers] thus generated, the harbormaster estimated that each of the ship’s scallops possessed an average of 139 of a pound of meat (that is, they were about seven percent lighter than the minimum requirement). Viewing this outcome as conclusive evidence that the weight standard had been violated, federal authorities at once confiscated 95 percent of the catch (which they then sold at auction). The fishing voyage was thus transformed into a financial catastrophe for its participants. The actual scallop weight measurements for each of the 18 sampled bags are listed in the table below. For ease of exposition, Barnett expressed each number as a multiple of of a pound, the minimum permissible average weight per scallop. Consequently, numbers below 1 indicate individual bags that do not meet the standard. The ship’s owner filed a lawsuit against the federal government, declaring that his vessel had fully complied with the weight standard. A Boston law firm was hired to represent the owner in legal proceedings, and Barnett was retained by the firm to provide statistical litigation support and, if necessary, expert witness testimony.

0.93

0.88

0.85

0.91

0.91

0.84

0.90

0.98

0.88

0.89

0.98

0.87

0.91

0.92

0.99

1.14

1.06

0.93

  1. Recall that the harbormaster sampled only 18 of the ship’s 11,000 bags of scallops. One of the questions the lawyers asked Barnett was, “Can a reliable estimate of the mean weight of all the scallops be obtained from a sample of size 18?” Give your opinion on this issue.
  2. As stated in the article, the government’s decision rule is to confiscate a catch if the sample mean weight of the scallops is less than 136 of a pound. Do you see any flaws in this rule?
  3. Develop your own procedure for determining whether a ship is in violation of the minimum-weight restriction. Apply your rule to the data. Draw a conclusion about the ship in question.
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