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The Uniform Distribution Quiz

12 questions math Grades 9-12

The question sheet

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  1. The uniform distribution is what type of probability distribution?

    • Exponential
    • Binomial
    • Discrete
    • Continuous
    Reveal answer

    Answer: Continuous

    Source evidence

    PDF page 338: The uniform distribution is a continuous probability distribution and is concerned with events that are equally likely to occur. When working out problems that have a uniform distribution, be careful to note if the data are inclusive or exclusive of endpoints.

  2. In X ~ U(a, b), what does a represent?

    • The mean of x
    • The lowest value of x
    • The standard deviation
    • The highest value of x
    Reveal answer

    Answer: The lowest value of x

    Source evidence

    PDF page 339: X ~ U(a, b) where a = the lowest value of x and b = the highest value of x.

  3. For the baby smiling times, what distribution is assumed?

    • U(0, 15)
    • U(0, 14)
    • U(0, 23)
    • U(1.5, 4)
    Reveal answer

    Answer: U(0, 23)

    Source evidence

    PDF page 339: We will assume that the smiling times, in seconds, follow a uniform distribution between zero and 23 seconds, inclusive. This means that any smiling time from zero to and including 23 seconds is equally likely. The histogram that could be constructed from the sample is an empirical distribution that closely matches the theoretical uniform distribution. Let X = length, in seconds, of an eight-week-old baby's smile. The notation for the uniform distribution is

    PDF page 339: b − a 1 For this example, X ~ U(0, 23) and f(x) =

  4. For the baby smiling example, the theoretical mean is:

    • 6.64 seconds
    • 11.50 seconds
    • 20.7 seconds
    • 11.49 seconds
    Reveal answer

    Answer: 11.50 seconds

    Source evidence

    PDF page 339: = 11.50 seconds and σ =

  5. For the baby smiling example, the theoretical standard deviation is:

    • 4.33 seconds
    • 6.23 seconds
    • 11.50 seconds
    • 6.64 seconds
    Reveal answer

    Answer: 6.64 seconds

    Source evidence

    PDF page 339: = 6.64 seconds. 2 12 Notice that the theoretical mean and standard deviation are close to the sample mean and standard deviation in this example.

  6. What is the 90th percentile for a baby's smiling time?

    • 13.5 seconds
    • 20.7 seconds
    • 18 seconds
    • 23 seconds
    Reveal answer

    Answer: 20.7 seconds

    Source evidence

    PDF page 341: k = (23)(0.90) = 20.7

  7. For bus wait time U(0,15), P(x < 12.5) equals:

    • 0.5000
    • 0.6000
    • 0.90
    • 0.8333
    Reveal answer

    Answer: 0.8333

    Source evidence

    PDF page 342: = 0.8333 ⎝15⎠ The probability a person waits fewer than 12.5 minutes is 0.8333.

  8. For bus wait time U(0,15), the average wait is:

    • 7.5 minutes
    • 4.3 minutes
    • 12.5 minutes
    • 13.5 minutes
    Reveal answer

    Answer: 7.5 minutes

    Source evidence

    PDF page 343: = = 7.5. On the average, a person must wait 7.5 minutes. 2 2

  9. For bus wait time U(0,15), the standard deviation is:

    • 13.5 minutes
    • 7.5 minutes
    • 4.3 minutes
    • 0.8333 minutes
    Reveal answer

    Answer: 4.3 minutes

    Source evidence

    PDF page 343: = 4.3. The standard deviation is 4.3 minutes. = 12 12

  10. For bus wait U(0,15), the 90th percentile is:

    • 13.5 minutes
    • 7.5 minutes
    • 20.7 minutes
    • 12.5 minutes
    Reveal answer

    Answer: 13.5 minutes

    Source evidence

    PDF page 343: k = (0.90)(15) = 13.5

    PDF page 343: The 90 percentile is 13.5 minutes. Ninety percent of the time, a person must wait at most 13.5 minutes.

  11. The 90th percentile k is sometimes called what?

    • A modal value
    • A mean value
    • A median value
    • A critical value
    Reveal answer

    Answer: A critical value

    Source evidence

    PDF page 343: k is sometimes called a critical value.

  12. For furnace repair U(1.5,4), P(x > 2) equals:

    • 0.8
    • 0.4
    • 0.3
    • 0.6
    Reveal answer

    Answer: 0.8

    Source evidence

    PDF page 346: P(x > 2) = (base)(height) = (4 – 2)(0.4) = 0.8

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