Ch07 Continuous Probability - Chapter 7 Continuous Probability Distributions True\/False 1 The Empirical Rule of probability can be applied to the

Ch07 Continuous Probability - Chapter 7 Continuous...

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Chapter 7 Continuous Probability Distributions True/False 1. The Empirical Rule of probability can be applied to the uniform probability distribution. Answer: False 2. Areas within a continuous probability distribution represent probabilities. Answer: True 3. The total area within a continuous probability distribution is equal to 100. Answer: False 4. The total area within any continuous probability distribution is equal to 1.00 Answer: True 5. For any continuous probability distribution, the probability, P(x), of any value of the random variable, X, can be computed. Answer: False 6. For any discrete probability distribution, the probability, P(x), of any value of the random variable, X, can be computed. Answer: True 7. The uniform probability distribution's standard deviation is proportional to the distribution's range. Answer: True 8. For any uniform probability distribution, the mean and standard deviation can be computed by knowing the maximum and minimum values of the random variable. Answer: True 9. In a uniform probability distribution, P(x) is constant between the distribution's minimum and maximum values. Answer: True 10. For a uniform probability distribution, the probability of any event is equal to 1/(b-a). Answer: False
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11. The uniform probability distribution is symmetric about the mode. Answer: False 12. The uniform probability distribution's shape is a rectangle. Answer: True 13. The uniform probability distribution is symmetric about the mean and median. Answer: True 14. Asymptotic means that the normal curve gets closer and closer to the X-axis but never actually touches it. Answer: True 15. A continuity correction factor compensates for estimating a discrete distribution with a continuous distribution. Answer: True 16. The normal curve falls off smoothly in either direction from the central value. Since it is asymptotic, the curve gets closer and closer to the X-axis, but never actually touches it. Answer: True 17. When referring to the normal probability distribution, there is not just one; there is a "family" of distributions. Answer: True 18. Some normal probability distributions have equal arithmetic means, but their standard deviations may be different. Answer: True 19. Some normal probability distributions have different arithmetic means and different standard deviations. Answer: True 20. Some normal probability distributions are positively skewed. Answer: False 21. For a normal probability distribution, about 95 percent of the area under normal curve is within plus and minus two standard deviations of the mean and practically all (99.73 percent) of the area under the normal curve is within three standard deviations of the mean. Answer: True
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22. The area under the normal curve within plus and minus one standard deviation of the mean is about 68.26%.
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