# IS 310 Exam #2 (chapter 6)

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The center of a normal curve is a. always equal to zero b. is the mean of the distribution c. cannot be negative d. is the standard deviation
b. is the mean of the distribution
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The probability that a continuous random variable takes any specific value a. is equal to zero b. is at least 0.5 c. depends on the probability density function d. is very close to 1.0
a. is equal to zero
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A normal distribution with a mean of 0 and a standard deviation of 1 is called a. a probability density function b. an ordinary normal curve c. a standard normal distribution d. None of these alternatives is correct.
c. a standard normal distribution
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The z score for the standard normal distribution a. is always equal to zero b. can never be negative c. can be either negative or positive d. is always equal to the mean
c. can be either negative or positive
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In a standard normal distribution, the probability that Z is greater than zero is a. 0.5 b. equal to 1 c. at least 0.5 d. 1.96
a. 0.5
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A negative value of Z indicates that a. the number of standard deviations of an observation is to the right of the mean b. the number of standard deviations of an observation is to the left of the mean c. a mistake has been made in computations, since Z cannot be negative d. the data has a negative mean
b. the number of standard deviations of an observation is to the left of the mean
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The uniform, normal, and exponential distributions are a. all continuous probability distributions b. all discrete probability distributions c. can be either continuous or discrete, depending on the data d. all the same distributions
a. all continuous probability distributions
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A value of 0.5 that is added and/or subtracted from a value of x when the continuous normal distribution is used to approximate the discrete binomial distribution is called a. 50% of the area under the normal curve b. continuity correction factor c. factor of conversion d. all of the alternatives are correct answers
b. continuity correction factor
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For a continuous random variable x, the probability density function f(x) represents a. the probability at a given value of x b. the area under the curve at x c. the area under the curve to the right of x d. the height of the function at x
d. the height of the function at x
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The uniform probability distribution is used with a. a continuous random variable b. a discrete random variable c. a normally distributed random variable d. any random variable, as long as it is not nominal
a. a continuous random variable
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For any continuous random variable, the probability that the random variable takes on exactly a specific value is a. 1.00 b. 0.50 c. any value between 0 to 1 d. almost zero
d. almost zero
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For the standard normal probability distribution, the area to the left of the mean is a. -0.5 b. 0.5 c. any value between 0 to 1 d. 1
b. 0.5
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Which of the following is not a characteristic of the normal probability distribution? a. The mean, median, and the mode are equal b. The mean of the distribution can be negative, zero, or positive c. The distribution is symmetrical d. The standard deviation must be 1
d. The standard deviation must be 1
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In a standard normal distribution, the range of values of z is from a. minus infinity to infinity b. -1 to 1 c. 0 to 1 d. -3.09 to 3.09
a. minus infinity to infinity
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For a uniform probability density function, a. the height of the function cannot be larger than one b. the height of the function is the same for each value of x c. the height of the function is different for various values of x d. the height of the function decreases as x increases
b. the height of the function is the same for each value of x
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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. different for each interval b. the same for each interval c. at least one d. None of these alternatives is correct.
b. the same for each interval
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The function that defines the probability distribution of a continuous random variable is a a. normal function b. uniform function c. either normal of uniform depending on the situation d. probability density function
d. probability density function
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When a continuous probability distribution is used to approximate a discrete probability distribution a. a value of 0.5 is added and/or subtracted from the area b. a value of 0.5 is added and/or subtracted from the value of x c. a value of 0.5 is added to the area d. a value of 0.5 is subtracted from the area
b. a value of 0.5 is added and/or subtracted from the value of x
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A continuous probability distribution that is useful in describing the time, or space, between occurrences of an event is a(n) a. normal probability distribution b. uniform probability distribution c. exponential probability distribution d. Poisson probability distribution
d. Poisson probability distribution
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The exponential probability distribution is used with a. a discrete random variable b. a continuous random variable c. any probability distribution with an exponential term d. an approximation of the binomial probability distribution
b. a continuous random variable
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Larger values of the standard deviation result in a normal curve that is a. shifted to the right b. shifted to the left c. narrower and more peaked d. wider and flatter
d. wider and flatter
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Which of the following is not a characteristic of the normal probability distribution? a. symmetry b. The total area under the curve is always equal to 1. c. 99.72% of the time the random variable assumes a value within plus or minus 1 standard deviation of its mean d. The mean is equal to the median, which is also equal to the mode.
c. 99.72% of the time the random variable assumes a value within plus or minus 1 standard deviation of its mean
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For a normal distribution, a negative value of z indicates a. a mistake has been made in computations, because z is always positive b. the area corresponding to the z is negative c. the z is to the left of the mean d. the z is to the right of the mean
c. the z is to the left of the mean
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The mean of a standard normal probability distribution a. is always equal to zero b. can be any value as long as it is positive c. can be any value d. is always greater than zero
a. is always equal to zero
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The standard deviation of a standard normal distribution a. is always equal to zero b. is always equal to one c. can be any positive value d. can be any value
b. is always equal to one
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A normal probability distribution a. is a continuous probability distribution b. is a discrete probability distribution c. can be either continuous or discrete d. must have a standard deviation of 1
a. is a continuous probability distribution
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A continuous random variable may assume a. all values in an interval or collection of intervals b. only integer values in an interval or collection of intervals c. only fractional values in an interval or collection of intervals d. all the positive integer values in an interval
a. all values in an interval or collection of intervals
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A continuous random variable is uniformly distributed between a and b. The probability density function between a and b is a. zero b. (a - b) c. (b - a) d. 1/(b - a)
d. 1/(b - a)
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If the mean of a normal distribution is negative, a. the standard deviation must also be negative b. the variance must also be negative c. a mistake has been made in the computations, because the mean of a normal distribution cannot be negative d. None of these alternatives is correct.
d. None of these alternatives is correct.
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For a standard normal distribution, the probability of z less than or equal to 0 is a. zero b. -0.5 c. 0.5 d. one
c. 0.5
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The highest point of a normal curve occurs at a. one standard deviation to the right of the mean b. two standard deviations to the right of the mean c. approximately three standard deviations to the right of the mean d. the mean
d. the mean
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A standard normal distribution is a normal distribution a. with a mean of 1 and a standard deviation of 0 b. with a mean of 0 and a standard deviation of 1 c. with any mean and a standard deviation of 1 d. with any mean and any standard deviation
b. with a mean of 0 and a standard deviation of 1
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An exponential probability distribution a. is a continuous distribution b. is a discrete distribution c. can be either continuous or discrete d. must be normally distributed