A light bulb manufacturer guarantees that the mean life of a certain type of light bulb is at least 747 hours. A random sample of 29 light bulbs has a mean life of 721 hours. Assume the population is normally distributed and the population standard deviation is 58 hours. At a = 0.02, do you have enough evidence to reject the manufacturer's claim? Complete parts (a) through (e). (a) Identify the null hypothesis and alternative hypothesis. O B. Ho: u> 747 Hai us 747 (claim) OC. Ho:H< 721 (claim) Ha: u2 721 O A. Ho: H2 747 (claim) Ha: H<747 O D. Ho:H= 747(claim) O E. Ho: Hs 721 OF. Ho:µ = 721 Hai H = 747 Ha: u> 721 (claim) Hai u = 721 (claim) (b) Identify the critical value(s). Use technology. Zo = (Use a comma to separate answers as needed. Round to two decimal places as needed.) Identify the rejection region(s). Choose the correct answer below. O A. O B. OC. Fail to reject Ho- Fail to reject Ho- Fail to reject Ho- Reject H- Reject Hg- Reject Ho Reject Ho- (c) Identify the standardized test statistic. Use technology. (Round to two decimal places as needed.) (d) Decide whether to reject or fail to reject the null hypothesis, and (e) interpret the decision in the context of the original claim. O A. Reject Ho. There is sufficient evidence to reject the claim that mean bulb O B. Reject Ho. There is not sufficient evidence to reject the claim that mean life is at least 747 hours. bulb life is at least 747 hours. OC. Fail to reject Hn. There is sufficient evidence to reject the claim that O D. Fail to reject Hn. There is not sufficient evidence to reject the claim that mean bulb life is at least 747 hours. mean bulb life is at least 747 hours.
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
light bulb manufacturer guarantees that the mean life of a certain type of light bulb is at least
hours. A random sample of
light bulbs has a mean life of
hours. Assume the population is
hours. At
do you have enough evidence to reject the manufacturer's claim? Complete parts (a) through (e).
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