Identify each of the following statements as either TRUE or FALSE.

a) The largest value a binomial random variable can be is n + 1.

b) binomial random variable, X, can take on a total of n possible values.

c) If the probability of success is greater than zero, then the mean of a binomial random variable is greater than the variance.

d) In a binomial distribution, each trial can have one of two possible outcomes.

e) In a binomial distribution, the random variable X is a count of the number of successes.

f) The probability of success in a geometric distribution remains constant between each trial.

g) In a geometric distribution, the random variable X can take on a countably infinite number of values.

h) In a geometric distribution, if the first success occurs on the Xth trial, then on the first X - 1 trials there must have been only a small number of successes.

i) If the probability of success in a geometric distribution is greater than 0.5, then the variance is greater than the mean.

j) There are a finite number of independent trials in a geometric distribution.

k) In a hypergeometric distribution, if x is the number of successes in a sample size of n, then n - x is the number of failures in the sample.

l) The hypergeometric distribution depends on the population size, the sample size, and number of successes within the population.

m) If X is a hypergeometric random variable, then X can take on n different values.

n) In a hypergeometric distribution, the trials are independent of each other.

o) The hypergeometric distribution is not appropriate to use whenever the probability of success changes depending on the outcome of previous trials.

p) A Poisson distribution can be applied when counting the number of times an event of interest occurs over time, volume, area or distance.

q) One condition required of a Poisson random variable is that the events of interest are occurring independently over time, volume, area or distance.

r) The mean of a Poisson random variable can be negative.

s) Because there is no fixed upper-limit for the value of a Poisson random variable, X, it is not a discrete random variable.

t) The smallest value a Poisson random variable can be is 0.