1. A continuous random variable is uniformly istributed between a and b. The probability destiny function between a and b is ____ A. 1/(b-a)
2. A continuous random variable may assume ___ A. All values in an interval or collection of intervals
3. A normal probability distribution _____. A. is a continuous probability distribution
4. A standard normal distribution is a normal distribution with ____ A. a mean of 0 and a standard deviation of 1
5. A uniform probability distribution is a continuous probability distribution where the probability that the random variable assumes a value in any interval of equal length is ___ A. the same for each interval
6. Assume z is a standard normal random variable. Then P(1.05 ≤ z ≤ 2.13) equals _____.A. 0.1303
7. Assume z is a standard normal random variable. Then P(1.20 ≤ z ≤ 1.85) equals _____. A. 0.0829
8. Assume z is a standard normal random variable. Then P(-1.20 ≤ z ≤ 1.50) equals _____. A. 0.8181
9. Assume z is a standard normal random variable. Then P(1.41 < z < 2.85) equals _____. A. none of the answers are correct
10. Assume z is a standard normal random variable. Then P(-1.5 ≤ z ≤ 1.09) equals _____. A. 0.7953
11. Assume z is a standard normal random variable. Then P(-1.96 ≤ z ≤ -1.4) equals ____ A. 0.0558
12. Assume z is a standard normal random variable. What is the value of z if the area between -z and z is .754? A. 1.16
13. Assume z is a standard normal random variable. What is the value of z if the area to the right of z is .9803? A. -2.06
Correct
14. For a continuous random variable x, the probability destiny function f(x) represents ___ A. the heigh of the function at x
15. For a standard normal distribution, the area to the left of the mean is ____ A. 0.5
16. For a standard normal distribution, the probability of obtaining a z value between -2.4 and -2.0 is _____. A. .0146
17. For a standard normal distribution, the probability of obtaining a z value of less than 1.6 is _____. A. 0.9452
18. For a standard normal distribution, the probability of obtaining a z value between -1.9 and 1.7 is _____. A. 0.9267
19. For a standard normal distribution, the probability of z ≤ 0 is _____. A. 0.5
20. For a uniform probability destiny function, the heigh of the function ____ A. is the same for each value of x
21. For any continuous random variable, the probability that the random variable takes on exactly a specific value is ___ A. 0
22. Given that z is a standard normal random variable, what is the value of z if the area to the right of z is .1112? A. 1.22
23. Given that z is a standard normal random variable, what is the value of z if the area to the right of z is .1401? A. 1.08
24. Given that z is a standard normal random variable, what is the value of z if the area to the left of z is .9382? A. 1.54
25. If the mean of a normal distribution is negative, ____ A. none of the answers is correct
26. In a standard normal distribution, a negative value of z indicated ____ A. the z is to the left of the mean
27. Larger values of the standard deviation result in a normal curve that is ____ A. wide and flatter
28. Refer to Exhibit 6-1. The mean of x is _____. A. 24
29. Refer to Exhibit 6-1. The probability density function has what value in the interval between 20 and 28? A. 0.125
30. Refer to Exhibit 6-1. The probability that x will take on a value between 21 and 25 is_____. A. 0.5
31. Refer to Exhibit 6-1. The probability that x will take on a value of at least 26 is _____. A. 0.250
32. Refer to Exhibit 6-1. The variance of x is approximately _____. A. 5.333
33. Refer to Exhibit 6-2. The probability that her trip will take exactly 50 minutes is _____. A. 0
34. Refer to Exhibit 6-2. The probability that her trip will take longer than 60 minutes is _____. A. .60
35. Refer to Exhibit 6-2. The probability that she will finish her trip in 80 minutes or less is _____. A. 0.8
36. Refer to Exhibit 6-2. What is the random variable in this experiment? A. Travel time
37. Refer to Exhibit 6-3. The probability of a player weighing less than 250 pounds is _____. A. 0.9772
38. Refer to Exhibit 6-3. The probability of a player weighing more than 241.25 pounds is ___ A. 0.0495
39. Refer to Exhibit 6-3. What is the random variable in this experiment? A. weight of the f ootball player
40. Suppose x is a normally distributed random variable with a mean of 8 and a standard deviation of 4. The probability that x is between 1.48 and 15.56 is _____. A. 0.9190
41. Suppose x is a normally distributed random variable with a mean of 5 and a variance of 4. The probability that x is greater than 10.52 is _____. A. 0.0029
42. Suppose x is a normally distributed random variable with a mean of 12 and a standard deviation of 3. The probability that x equals 19.62 is _____. A. 0
43. Suppose x is a normally distributed random variable with a mean of 22 and a standard deviation of 5. The probability that x is less than 9.7 is _____. A. 0.0069
44. The ages of students at a university are normally distributed with a mean of 21. What percentage of the student body is at least 21 years old? A. 50%
45. The assembly time for a product is uniformly distributed between 6 and 10 minutes. The probability density function has what value in the interval between 6 and 10? A. .25
46. The assembly time for a product is uniformly distributed between 6 and 10 minutes. The probability of assembling the product between 7 and 9 minutes is _____. A. .50
47. The assembly time for a product is uniformly distributed between 6 and 10 minutes. The probability of assembling the product in less than 6 minutes is _____. A. 0
48. The assembly time for a product is uniformly distributed between 6 and 10 minutes. The probability of assembling the product in 7 minutes or more is _____. A. .75
49. The assembly time for a product is uniformly distributed between 6 and 10 minutes. The expected assembly time (in minutes) is _____. A. 8
50. The assembly time for a product is uniformly distributed between 6 and 10 minutes. The standard deviation of assembly time (in minutes) is approximately _____. A. none of the answers is correct
51. The form of the continuous uniform probability distribution is ___ A. rectangular
52. The highest point of a normal curve occurs at _____ A. one standard deviation to the right of the mean
53. The mean of a standard normal probability distribution _____. A. None of the answers are
54. The mean, median, and mode have the same value for which of the following Probability distribution? A. normal
55. The Probability destiny function for a uniform distribution randing between 2 nd 6 is ___ A.25
56. The probability distribution that can be described by just one parameter is the ___ distribution A. exponential
57. The random variable x is knwon to be uniformly distributed between 70 and 90. The probability of x having a value between 80 and 95 is ___ A. .5
58. The standard deviation of a standard normal distribution _____. A. is always equal to 1
59. The uniform probability distribution is used with ___ A. a continuous random variable
60. There is a lower limit but no upper limit for a random variable that follows the ___ probability distribution A. exponential
61. What type of function defines the probability distribution of ANY continuous random variable? A. Probability destiny function
62. Whenever the probability is proportional to the length of the interval in which the random variable can assume a value, the random variable follows a(n) _____ distribution. A. uniform
63. Which of the following is NOT a characteristic of the normal probability distribution? A. The standard deviation must be 1
64. Which of the following is NOT a characteristic of the normal probability distribution? A. The graph of the curve is the shape of the rectangle
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