solns) 24/25 |BRAND NEW |CODE 22
Discrete random variables take on values across a continuum. - answer-FALSE
The probability mass function of a discrete random variable is a description of the
probabilities associated with each possible value of the random variable. - answer-
TRUE
The sum of all of the probabilities in a probability mass function equals unity. - answer-
TRUE
A probability mass function, f(x), is a non-decreasing function of x. - answer-FALSE
True or False? P(X = 3) can be written as P(X = 3) = {P(X = 0) + P(X = 1) + P(X = 2) +
P(X = 3)} - {P(X = 0) + P(X = 1) + P(X = 2)} - answer-TRUE
The cumulative distribution function, F(x), of a discrete random variable is the sum of all
of the probabilities that are less than or equal to x, where x is a specific value of the
discrete random variable, X. - answer-TRUE
A cumulative distribution function can be used to find the probability mass function of a
discrete random variable. - answer-TRUE
If a random variable, X, has only integer values, then the mean, E(X), will always be an
integer. - answer-FALSE
The mean of a discrete random variable is its expected value. - answer-TRUE
If the variances of two discrete random variables are equal, then the means are equal. -
answer-FALSE
The standard deviation of a discrete random variable is the square of its variance. -
answer-FALSE
True or False? X, the face value for the throw of a fair die, has the discrete uniform
distribution. - answer-TRUE
A discrete uniform random variable has equal probability assigned to each of its
possible values. - answer-TRUE
How many numerical values can a Binomial random variable, X, have? - answer-n+1
, True or False? If X is a Binomial random variable, then we can also obtain the mean
and variance using the following equations from section 3-3 - answer-TRUE
A Bernoulli trial is a random experiment with only two outcomes, success and failure. -
answer-TRUE
The binomial distribution arises from a series of Bernoulli trials. - answer-TRUE
The variance of a binomial random variable with parameters n and p is p(1 - p). -
answer-FALSE
Which of the following definitions of X demonstrates that X has the Geometric
Distribution? - answer-NONBINARY answers
True or False? If X is a Geometric random variable, then we can also obtain the mean
and variance using the following equations from section 3-3: - answer-TRUE
If X is the number of independent Bernoulli trials until the first success, the distribution
of X is geometric. - answer-TRUE
The distribution of the number of Bernoulli trials until the rth success is the negative
binomial distribution. - answer-TRUE
The negative binomial distribution has mean r/p. - answer-TRUE
The hypergeometric distribution is associated with sampling without replacement from a
finite population of N objects. - answer-TRUE
If X is a hypergeometric random variable with parameters n, K, and N, and p = K/N, then
the number of successes and the total number of objects are: - answer-K and N.
When the sample size, n, is large relative to the population size, N, the binomial
distribution can adequately approximate the hypergeometric distribution. - answer-
FALSE
The Poisson distribution is widely used as a model of the number of events in an
interval. - answer-TRUE
In a Poisson Process, the probability of an event in an interval depends on the length of
the interval, but not the location of the interval. - answer-TRUE
If the random variable, X, has a Poisson distribution with a mean of 4 events per minute,
the mean number of events per hour is: - answer-none of the above