Requests to a Web server. In Exercise $4.175$ (p. 258) you learned that Brighton Webs LTD modeled the arrival time of requests to a Web server within each hour, using a uniform distribution. Specifically, the number of seconds $x$ from the start of the hour that the request is made is uniformly distributed between 0 and 3,600 seconds. In a random sample of $n=60$ Web server requests, let $\bar{x}$ represent the sample mean number of seconds from the start of the hour that the request is made. Find the probability that $\bar{x}$ is between 1,700 and 1,900 seconds.

Requests to a Web server. In Exercise $4.175$ (p. 258) you learned that Brighton Webs LTD modeled the arrival time of requests to a Web server within each hour, using a uniform distribution. Specifically, the number of seconds $x$ from the start of the hour that the request is made is uniformly distributed between 0 and 3,600 seconds. In a random sample of $n=60$ Web server requests, let $\bar{x}$ represent the sample mean number of seconds from the start of the hour that the request is made. Describe the shape of the sampling distribution of $\bar{x}$.

According to Brighton Webs LTD, a British company that specializes in data analysis, the arrival time of requests to a Web server within each hour can be modeled by a uniform distribution ( www.brighton-webs. co.uk ). Specifically, the number of seconds x from the start of the hour that the request is made is uniformly distributed between 0 and 3,600 seconds. Find the probability that a request is made to a Web server sometime during the last 15 minutes of the hour.

Study of why EMS workers leave the job. A study of fulltime emergency medical service (EMS) workers published in the Journal of Allied Health (Fall 2011) found that only about 3% leave their job in order to retire. (See Exercise $3.45$, p. 158.) Assume that the true proportion of all fulltime EMS workers who leave their job in order to retire is $p=.03$. In a random sample of 1,000 full-time EMS workers, let $\hat{p}$ represent the proportion who leave their job in order to retire. Compute $P(\hat{p}>.025)$. Interpret this result.

Study of why EMS workers leave the job. A study of fulltime emergency medical service (EMS) workers published in the Journal of Allied Health (Fall 2011) found that only about $3 \%$ leave their job in order to retire. (See Exercise $3.45$, p. 158.) Assume that the true proportion of all fulltime EMS workers who leave their job in order to retire is $p=.03$. In a random sample of 1,000 full-time EMS workers, let $\hat{p}$ represent the proportion who leave their job in order to retire. Describe the properties of the sampling distribution of $\hat{p}$.

Large stadiums rely on backup generators to provide electricity in the event of a power failure. Assume that emergency backup generators fail 22% of the times when they are needed (based on data from Arshad Mansoor, senior vice president with the Electric Power Research Institute). A stadium has three backup generators so that power is available if at least one of them works in a power failure. Find the probability of having at least one of the backup generators working given that a power failure has occurred. Does the result appear to be adequate for the stadium's needs?

Study of why EMS workers leave the job. A study of fulltime emergency medical service (EMS) workers published in the Journal of Allied Health (Fall 2011) found that only about 3% leave their job in order to retire. (See Exercise $3.45$, p. 158.) Assume that the true proportion of all fulltime EMS workers who leave their job in order to retire is $p=.03$. In a random sample of 1,000 full-time EMS workers, let $\hat{p}$ represent the proportion who leave their job in order to retire. Compute $P(\hat{p}<.05)$. Interpret this result.

Study of why EMS workers leave the job. An investigation into why emergency medical service (EMS) workers leave the profession was published in the Journal of Allied Health (Fall 2011). The researchers surveyed a sample of 244 former EMS workers, of which 127 were fully compensated while on the job, 45 were partially compensated, and 72 had noncompensated volunteer positions. The numbers of EMS workers who left because of retirement were 7 for fully compensated workers, 11 for partially compensated workers, and 10 for noncompensated volunteers. One of the 244 former EMS workers is selected at random. Find the probability that the former EMS worker was not fully compensated while on the job.

Three-year-old C.E. is admitted to the emergency department (ED) fast track clinic. Her mother tells the nurse that C.E. has had a low-grade fever for 2 days and is complaining of ear pain and a sore throat. C.E.'s mother states that C.E.'s appetite has been "off;' but she has been drinking and using the bathroom as usual. As you get C.E. settled in the exam room, you suspect C.E may have otitis media (OM).
Place an arrow where you suspect fluid would be found.

Assume that x is a binomial random variable with n = 100 and p = .5. Use the normal probability distribution to approximate the following probabilities:

$$P ( 50 \leq x \leq 65 )$$

(a) Why do economists measure real GDP per capita? (b) Why does real GDP per capita provide a better way to compare the economies.of.two different nations than does real GDP alone?

Performance of stock screeners. In Exercise 2.44 (p. 71) you learned that stock screeners are automated tools used by investment companies to help clients select a portfolio of stocks to invest in. The table below lists the annualized percentage return on investment (as compared to the Standard & Poor's 500 Index) for 13 randomly selected stock screeners provided by the American Association of Individual Investors (AAII). What assumption about the distribution of the annualized percentage returns on investment is required for the inference, part b, to be valid? Is this assumption reasonably satisfied?

Cell phone use by drivers.Studies have shown that drivers who use cell phones while operating a motor passenger vehicle increase their risk of an accident. Nevertheless, drivers continue to make cell phone calls while driving. A June 2011 Harris Poll of 2,163 adults found that $60 \%(1,298$ adults) use cell phones while driving. Give a practical interpretation of the interval, part b.

Cell phone use by drivers. Studies have shown that drivers who use cell phones while operating a motor passenger vehicle increase their risk of an accident. Nevertheless, drivers continue to make cell phone calls while driving. A June 2011 Harris Poll of 2,163 adults found that $60 \%(1,298$ adults) use cell phones while driving. Give a point estimate of $p$, the true driver cell phone use rate (i.e., the proportion of all drivers who are using a cell phone while operating a motor passenger vehicle).