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Question: Hotel guest satisfaction. Refer to the results of the 2015 North American Hotel Guest Satisfaction Index Study, Exercise 4.49 (p. 239). Recall that 15% of hotel guests were “delighted” with their experience (giving a rating of 10 out of 10); of these guests, 80% stated they would “definitely” recommend the hotel. In a random sample of 100 hotel guests, find the probability that fewer than 10 were delighted with their stay and would recommend the hotel.

Short Answer

Expert verified

The probability that fewer than 10 () delighted with their stay and would recommend the hotel is 0.2676.

Step by step solution

01

Given information

Let p denotes the proportion of guests who were delighted with their stay and would recommend the hotel.

15% of guests were delighted with their experience, and of these, 80% would recommend the hotel

Therefore,

.

A random sample of size 100 is selected.

02

Computing the required probability

The probability that fewer than 10 () delighted with their stay and would recommend the hotel obtain as follows

Pp^<.10=Pp^-pσp^<0.10-pσp^=PZ<0.10-0.120.12×0.88100=PZ<-0.020.001056=PZ<-0.020.0324=PZ<-0.62=0.2676

In the z-table, the value at the intersection of -0.60 and 0.02 is the required probability.

Therefore, the required probability is 0.2676.

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Most popular questions from this chapter

Analysis of supplier lead time. Lead timeis the time betweena retailer placing an order and having the productavailable to satisfy customer demand. It includes time for placing the order, receiving the shipment from the supplier, inspecting the units received, and placing them in inventory. Interested in average lead time,, for a particular supplier of men’s apparel, the purchasing department of a national department store chain randomly sampled 50 of the supplier’s lead times and found= 44 days.

  1. Describe the shape of the sampling distribution ofx¯.
  2. If μand σare really 40 and 12, respectively, what is the probability that a second random sample of size 50 would yieldx¯ greater than or equal to 44?
  3. Using the values forμ and σin part b, what is the probability that a sample of size 50 would yield a sample mean within the interval μ±2σn?

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 a random sample of n measurements is selected from a population with u=100mean and variance role="math" localid="1657967387987" σ2=100. For each of the following values of n, give the mean and standard deviation of the sampling distribution of the sample mean.

  1. role="math" localid="1657967260825" n=4
  2. n=25
  3. n=100
  4. n=50
  5. n=500
  6. n=1000

Consider the population described by the probability distribution shown below.

The random variable x is observed twice. If these observations are independent, verify that the different samples of size 2 and their probabilities are as shown below.

a. Find the sampling distribution of the sample meanx.

b. Construct a probability histogram for the sampling distribution ofx.

c. What is the probability thatxis 4.5 or larger?

d. Would you expect to observe a value ofxequal to 4.5 or larger? Explain.

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

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