For any continuous random variable, the probability that the random variable tak
ID: 1134285 • Letter: F
Question
For any continuous random variable, the probability that the random variable takes on exactly a specific value is
1.00
0.50
any value between 0 to 1
almost zero
1 points
QUESTION 7
For the standard normal probability distribution, the area to the left of the mean is
-0.5
0.5
any value between 0 to 1
1
1 points
QUESTION 8
In a standard normal distribution, the range of values of z is from
minus infinity to infinity
-1 to 1
0 to 1
-3.09 to 3.09
1 points
QUESTION 9
The mean of a standard normal probability distribution
is always equal to zero
can be any value as long as it is positive
can be any value
is always greater than zero
1 points
QUESTION 10
A method of assigning probabilities based on historical data is called the
classical method
subjective method
relative frequency method
historical method
1 points
QUESTION 11
A method of assigning probabilities based upon judgment is referred to as the
relative method
probability method
classical method
subjective method
1 points
QUESTION 12
A continuous random variable may assume
any value in an interval or collection of intervals
only integer values in an interval or collection of intervals
only fractional values in an interval or collection of intervals
only the positive integer values in an interval
1 points
QUESTION 13
A description of the distribution of the values of a random variable and their associated probabilities is called a
probability distribution
random variance
random variable
expected value
1 points
QUESTION 14
A numerical description of the outcome of an experiment is called a
descriptive statistic
probability function
variance
random variable
1 points
QUESTION 15
A random variable that can assume only a finite number of values is referred to as a(n)
infinite sequence
finite sequence
discrete random variable
discrete probability function
1 points
QUESTION 16
A weighted average of the value of a random variable, where the probability function provides weights is known as
a probability function
a random variable
the expected value
random function
1 points
QUESTION 17
An experiment consists of determining the speed of automobiles on a highway by the use of radar equipment. The random variable in this experiment is a
discrete random variable
continuous random variable
complex random variable
simplex random variable
1 points
QUESTION 18
The expected value of a random variable is
the value of the random variable that should be observed on the next repeat of the experiment
the value of the random variable that occurs most frequently
the square root of the variance
None of these alternatives is correct.
1 points
QUESTION 19
The number of customers that enter a store during one day is an example of
a continuous random variable
a discrete random variable
either a continuous or a discrete random variable, depending on the number of the customers
either a continuous or a discrete random variable, depending on the gender of the customers
1 points
QUESTION 20
The standard deviation is the
variance squared
square root of the sum of the deviations from the mean
same as the expected value
positive square root of the variance
1 points
QUESTION 21
The variance is a measure of dispersion or variability of a random variable. It is a weighted average of the
square root of the deviations from the mean
square root of the deviations from the median
squared deviations from the median
squared deviations from the mean
1 points
QUESTION 22
The weight of an object is an example of
a continuous random variable
a discrete random variable
either a continuous or a discrete random variable, depending on the weight of the object
either a continuous or a discrete random variable depending on the units of measurement
1 points
QUESTION 23
Variance is
a measure of the average, or central value of a random variable
a measure of the dispersion of a random variable
the square root of the standard deviation
the sum of the squared deviation of data elements from the mean
1 points
QUESTION 24
Which of the following statements about a discrete random variable and its probability distribution are true?
Values of the random variable can never be negative.
Some negative values of f(x) are allowed as long as Sf(x) = 1.
Values of f(x) must be greater than or equal to zero.
The values of f(x) increase to a maximum point and then decrease.
1 points
QUESTION 25
A continuous random variable is uniformly distributed between a and b. The probability density function between a and b is
zero
(a - b)
(b - a)
1/(b - a)
1 points
QUESTION 26
A continuous random variable may assume
all values in an interval or collection of intervals
only integer values in an interval or collection of intervals
only fractional values in an interval or collection of intervals
all the positive integer values in an interval
1 points
QUESTION 27
A normal probability distribution
is a continuous probability distribution
is a discrete probability distribution
can be either continuous or discrete
must have a standard deviation of 1
1 points
QUESTION 28
A standard normal distribution is a normal distribution
with a mean of 1 and a standard deviation of 0
with a mean of 0 and a standard deviation of 1
with any mean and a standard deviation of 1
with any mean and any standard deviation
1 points
QUESTION 29
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
different for each interval
the same for each interval
at least one
None of these alternatives is correct.
1 points
QUESTION 30
For a continuous random variable x, the probability density function f(x) represents
the probability at a given value of x
the area under the curve at x
the area under the curve to the right of x
the height of the function at x
1 points
QUESTION 31
For a standard normal distribution, a negative value of z indicates
a mistake has been made in computations, because z is always positive
the area corresponding to the z is negative
the z is to the left of the mean
the z is to the right of the mean
1 points
QUESTION 32
If the mean of a normal distribution is negative,
the standard deviation must also be negative
the variance must also be negative
a mistake has been made in the computations, because the mean of a normal distribution can not be negative
None of these alternatives is correct.
1 points
QUESTION 33
Larger values of the standard deviation result in a normal curve that is
shifted to the right
shifted to the left
narrower and more peaked
wider and flatter
1 points
QUESTION 34
The function that defines the probability distribution of a continuous random variable is a
normal function
uniform function
either normal of uniform depending on the situation
probability density function
1 points
QUESTION 35
The highest point of a normal curve occurs at
one standard deviation to the right of the mean
two standard deviations to the right of the mean
approximately three standard deviations to the right of the mean
the mean
1 points
QUESTION 36
The standard deviation of a standard normal distribution
is always equal to zero
is always equal to one
can be any positive value
can be any value
1 points
QUESTION 37
Which of the following is not a characteristic of the normal probability distribution?
The mean, median, and the mode are equal
The mean of the distribution can be negative, zero, or positive
The distribution is symmetrical
The standard deviation must be 1
1.00
0.50
any value between 0 to 1
almost zero
Explanation / Answer
6) The asnwer is D -) almost zero
that is For any continuous random variable, the probability that the random variable takes on exactly a specific value is almost zero.
7) The asnwer is B -) 0.5
8) The asnwer is A -) Minus infinity to infinity
9) The asnwer is A -) is always equal to zero
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