A contract between a manufacturer and a consumer of light bulbs specifies that the mean lifetime of the bulbs must be at least 1000 hours. As part of the quality assurance program, the manufacturer will institute an inspection program for each day's production of 10,000 units. An ordinary testing procedure is difficult since 1000 hours is over 41 days! Since the lifetime of a bulb decreases as the voltage applied increases, a common procedure is to perform an accelerated lifetime test in which the bulbs are lit using 400 volts (compared to the usual 110 volts). At such a voltage, a 1000-hour bulb is expected to last only 3 hours. This is a well-known procedure, and both sides have agreed that the results from the accelerated test will be a valid indicator of lifetime of the bulb.

The manufacturer will test the hypotheses H0 : µ = 3 versus Ha: µ < 3 at the α = 0.01 significance level with a simple random sample of 100 bulbs.

a. Describe what a Type I error would be in this context.
b. Describe what a Type II error would be in this context.
c. Which error—Type I or Type II—is likely to do more damage to the manufacturer’s relationship with the consumer? Explain.

Answer:

Follows are the solution to the given points:

Step-by-step explanation:

In point a:

In this sense, describe what type of error I will be.

Type I error: to conclude that perhaps the mean bulb life would be less than three hours when it becomes (at least) 3 hours.

In point b:

Describe throughout this context what the Type II error becomes.

An error of type II: never assuming that its bulbs' mean lifetime is much less than 3 hours. three hours at least

In point c:

What error — type I and type II — would further impact the interaction between the manufacturer and the customer?

A Type II error is probably further problematic because it means that even the buyer will buy bulbs that do not last long.

According to the DuPont 2012 Global Automotive Color Popularity Report, 23% of all cars manufactured in 2012 were white. In a random sample of 100 cars parked in long-term parking at Philadelphia International Airport, 19% of the cars were white. Identify the underlined values as parameters or statistics and give the appropriate variable. Spell out phat, x-bar, mu, sigma for the variable names. Which of the following statements istrue?

a. 19% and 23% are parameters, 100 is a statistic.
b. 23% is a parameter, 19% is a statistic.
c. 23% is a statistic, 19% is a parameter.
d. 19% and 23% are statistics, 100 is neither a parameter nor a statistic.
e. 19%, 23%, and 100 are all statistics.

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