STAT. TECH. IN BUSINESS + ECON LOOSELEAF
STAT. TECH. IN BUSINESS + ECON LOOSELEAF
18th Edition
ISBN: 9781264261765
Author: Lind
Publisher: MCG
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Problem 3 In their lab, engineer Daniel and Paulina are desperately trying to perfect time travel. But the problem is that their machine still struggles with power inconsistencies-sometimes generating too little energy, other times too much, causing unstable time jumps. To prevent catastrophic misjumps into the Jurassic era or the far future, they must calibrate the machine's power output. After extensive testing, they found that the time machine's power output follows a normal distribution, with an average energy level of 8.7 gigawatts and a standard deviation of 1.2 gigawatts. The Time Travel Safety Board has set strict guidelines: For a successful time jump, the machine's power must be between 8.5 and 9.5 gigawatts. What is the probability that a randomly selected time jump meets this precision requirement? Daniel suggests that adjusting the mean power output could improve time-travel accuracy. Can adjusting the mean reduce the number of dangerous misjumps? If yes, what should the…
Problem 5 ( Marybeth is also interested in the experiment from Problem 2 (associated with the enhancements for Captain America's shield), so she decides to start a detailed literature review on the subject. Among others, she found a paper where they used a 2"(4-1) fractional factorial design in the factors: (A) shield material, (B) throwing mechanism, (C) edge modification, and (D) handle adjustment. The experimental design used in the paper is shown in the table below. a. Run A B с D 1 (1) -1 -1 -1 1 2 a 1 -1 -1 1 3 bd -1 1 -1 1 4 abd 1 1 -1 1 5 cd -1 -1 1 -1 6 acd 1 -1 1 -1 7 bc -1 1 1 -1 abc 1 1 1 -1 paper? s) What was the generator used in the 2"(4-1) fractional factorial design described in the b. Based on the resolution of this design, what do you think about the generator used in the paper? Do you think it was a good choice, or would you have selected a different one? Explain your answer in detail.
Suppose we wish to test the hypothesis that women with a sister’s history of breast cancer are at higher risk of developing breast cancer themselves. Suppose we assume that the prevalence rate of breast cancer is 3% among 60- to 64-year-old U.S. women, whereas it is 5% among women with a sister history. We propose to interview 400 women 40 to 64 years of age with a sister history of the disease. What is the power of such a study assuming that the level of significance is 10%?             I only need help writing the null and alternative hypotheses.
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