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1.         A continuous random variable may assume

a.         any value 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.         only the positive integer values in an interval      

2.         A random variable that can assume only a finite number of values is referred to as a(n)

a.         infinite sequence

b.         finite sequence

c.         discrete random variable

d.         discrete probability function          

3.         The weight of an object, measured in grams, is an example of

a.         a continuous random variable

b.         a discrete random variable

c.         either a continuous or a discrete random variable, depending on the weight of the object

d.         either a continuous or a discrete random variable depending on the units of measurement

4          A description of how the probabilities are distributed over the values the random variable can assume is called a

a.         probability distribution

b.         probability function

c.         random variable

d.         expected value        

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5.         A description of how the probabilities are distributed over the values the random variable can assume is called a

a.         probability distribution

b.         probability function

c.         random variable

d.         expected value

6.         A measure of the average value of a random variable is called a(n)

a.         variance

b.         standard deviation

c.         expected value

d.         None of the answers is correct.

7.         A weighted average of the value of a random variable, where the probability function provides weights is known as

a.         a probability function

b.         a random variable

c.         the expected value

d.         None of the answers is correct     

8.         Variance is

a.         a measure of the average, or central value of a random variable

b.         a measure of the dispersion of a random variable

c.         the square root of the standard deviation

d.         the sum of the deviation of data elements from the mean

9.         The variance is a weighted average of the

a.         square root of the deviations from the mean

b.         square root of the deviations from the median

c.         squared deviations from the median

d.         squared deviations from the mean


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10.       The standard deviation is the

a.         variance squared

b.         square root of the sum of the deviations from the mean

c.         same as the expected value

d.         positive square root of the variance

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Chapter 6

11.       Whenever the probability is proportional to the length of the interval in which the random variable can assume a value, the random variable is

a.         uniformly distributed

b.         normally distributed

c.         exponentially distributed

d.         Poisson distributed

12.       The form of the continuous uniform probability distribution is

a.         triangular

b.         rectangular

c.         bell-shaped

d.         a series of vertical lines

13.       The mean, median, and mode have the same value for which of the following probability distributions?

a.         uniform

b.         normal

c.         exponential

d.         Poisson

14.       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

15.       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.         zero

16.       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

              17.       For a uniform probability density function, the height of the function

a.

cannot be larger than one

b.

is the same for each value of x

c.

is different for various values of x

d.

decreases as x increases

18.       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

19.       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             

20.       For a standard normal distribution, the probability of z  0 is

a.         zero

b.         -0.5

c.         0.5

d.         one