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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A researcher gathered a sample of participants who volunteered for a studying of phobias. She measured anxiety level of participants as they viewed photos of spiders and again when they viewed puppies. Which statistical test is appropriate for this study and why?
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Why is Data literacy important when evaluating sources from a study?
Color blindness, or dyschromatopsia, is a form of genetic deficiency in color perception. The condition is much more prevalent among males than females, pointing to a genetic connection with the X chromosome. The frequency of dyschromatopsia in the Caucasian American male population is about 7%. However, it is thought that this proportion might be smaller among males of other ethnicities. We want to estimate the proportion of Asian American males who are color-blind. How large a sample size do we need in order to obtain a 95% confidence interval with a margin of error no greater than 5%, or 0.05? Use 0.5 for p̂.
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Check My Work (5 remaining) Each year, over 2 million people in the United States become infected with bacteria that are resistant to antibiotics. In particular, the Centers of Disease Control and Prevention has launched studies of drug-resistant gonorrhea (CDC.gov website). Of 142 cases tested in Alabama, 9 were found to be drug-resistant. Of 268 cases tested in Texas, 5 were found to be drug-resistant. Do these data suggest a statistically significant difference between the proportions of drug- resistant cases in the two states? Use a 0.02 level of significance. What is the p-value, and what is your conclusion? Test statistic = (to 2 decimals) p-value = (to 4 decimals) Conclusion: Reject the null hypothesis Choose the correct option. There is a significant difference in drug resistance between the two states. Alabama has the higher drug resistance rate. True

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You'd like to test if coffee consumption (coffee drinkers, non-drinkers) affects differences in heart attack risk one year later (heart attack, no heart attack).