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Assuming you mean random variable here.
A random variable is term that can take have different values. for example a random variable x that represent the out come of rolling a dice, that is x can equal 1,2,3,4,5,or 6.
Think of probability distribution as the mapping of likelihood of the out comes from an experiment. In the dice case, the probability distribution will tell you that there 1/6 the time you will get 1, 2,3....,or 6. this is called uniform distribution since all the out comes have that same probability of occurring.
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What the difference between a probability distribution and a probability function?
None. The full name is the Probability Distribution Function (pdf).
What the difference and relationship between a probability distribution and a probability function?
They are the same. The full name is the Probability Distribution Function (pdf).
What is the difference between a probability mass function and a probability density function?
The probability mass function is used to characterize the distribution of discrete random variables, while the probability density function is used to characterize the distribution of absolutely continuous random variables. You might want to read more about this at www.statlect.com/prbdst1.htm (see the link below or on the right)
What is the difference between probability distribution and probability density function?
A probability density function assigns a probability value for each point in the domain of the random variable. The probability distribution assigns the same probability to subsets of that domain.
What is the difference between the normal distribution and Poisson distribution?
The normal distribution is a continuous probability distribution that describes the distribution of real-valued random variables that are distributed around some mean value.The Poisson distribution is a discrete probability distribution that describes the distribution of the number of events that occur within repeated fixed time intervals, where the mean frequency is a known value, and each interval is independent of the prior interval(s)/event(s).
The usual sampling distributionof the difference between means is a what?
There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.
What is the difference between a probability density curve and cummulative distribution function?
what is density curve
What is an important difference between the uniform and normal probability distributions?
The uniform distribution is limited to a finite domain, the normal is not.
Difference between a random variable and a probability distribution is?
A random variable is a variable that can take different values according to a process, at least part of which is random.For a discrete random variable (RV), a probability distribution is a function that assigns, to each value of the RV, the probability that the RV takes that value.The probability of a continuous RV taking any specificvalue is always 0 and the distribution is a density function such that the probability of the RV taking a value between x and y is the area under the distribution function between x and y.
Distinguish between binomial distribution and normal distribution?
Normal distribution is the continuous probability distribution defined by the probability density function. While the binomial distribution is discrete.
How does a discrete probability distribution differ from a continuous probability distribution?
A discrete probability distribution is defined over a set value (such as a value of 1 or 2 or 3, etc). A continuous probability distribution is defined over an infinite number of points (such as all values between 1 and 3, inclusive).
What is the difference between dependent and independent events in terms of probability?
What is the difference between dependant and independent events in terms of probability
