# Q:common probability distribution

this Q is from Schweser sample exam: 2. Which of following statements about common probability distribution is most likely correct? a. a probability distribution specifies the probability of the possible outcomes of a random variable. b. in a binominal probability distribution, each observation has only 2 possible outcomes that are mutually exclusive c, a discrete uniform distribution, the simplest of all probability distributions, is the distribution of equally likely outcomes d. a normal distribution is a discrete symmetric probability distribution that is completely described by 2 parameters: its mean and variance. Answer : d A normal distribution is a continuous symmetric probability distribution. --my problem is A,B. both of them seems correct.

D is surely not right because a normal distribution is not discrete (unfortunately the guy who bought the Marilyn Monroe video is). a) is kinda true but the sentence is all messed up. b) is not true because each observation is some number between 0 and n inclusive. c) is sorta true but that “simplest of all probability distributions” is gratuitous and not true (what makes a uniform simpler than a Bernoulli, for example?).

Read the question again…I believe it says which one is LEAST likely correct.

wyantjs Wrote: ------------------------------------------------------- > Read the question again…I believe it says > which one is LEAST likely correct. ------------------------------------------------------ no, i doubt checked, it is asking " most likely correct"

JoeyDVivre Wrote: ------------------------------------------------------- > D is surely not right because a normal > distribution is not discrete (unfortunately the > guy who bought the Marilyn Monroe video is). a) > is kinda true but the sentence is all messed up. > b) is not true because each observation is some > number between 0 and n inclusive. c) is sorta > true but that “simplest of all probability > distributions” is gratuitous and not true (what > makes a uniform simpler than a Bernoulli, for > example?). For c) What about for all x, in (-inf,0); (0,inf), p x = 0 ; for x=0, p(x)=1. That’s pretty simple

Yep that’s pretty simple too. In fact, your pdf is a “simple function” which makes it a good bet for simplest.