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What is the probability that a continuous random variable takes on a specific value?
Wiki User
∙ 11y ago
Zero.
Wiki User
∙ 11y ago
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How do you get the median of a continuous random variable?
You integrate the probability distribution function to get the cumulative distribution function (cdf). Then find the value of the random variable for which cdf = 0.5.
Is the gender of college students a discrete random variable a continuous random variable or not a random variable?
It is a discrete random variable.
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.
How do calculate the probability of at most?
For a discrete variable, you add together the probabilities of all values of the random variable less than or equal to the specified number. For a continuous variable it the integral of the probability distribution function up to the specified value. Often these values may be calculated or tabulated as cumulative probability distributions.
Can a random variable include the probability of an event?
No.
Does the probability that a continuous random variable take a specific value depend on the probability density function?
No. The probability that a continuous random variable takes a specific value is always zero.
Is temperature an example of continuous variable?
Yes. It is a continuous variable. As used in probability theory, it is an example of a continuous random variable.
Is the normal probability distribution applied to a continuous random variable?
Yes.
How do you get the median of a continuous random variable?
You integrate the probability distribution function to get the cumulative distribution function (cdf). Then find the value of the random variable for which cdf = 0.5.
Is the gender of college students a discrete random variable a continuous random variable or not a random variable?
It is a discrete random variable.
What are your expectations in mathematics?
In probability theory, the expectation of a discrete random variable X is the sum, calculated over all values that X can take, of : the product of those values and the probability that X takes that value. In the case of a continuous random variable, it is the corresponding integral.
Can the Poisson distribution be a continuous random variable or a discrete random variable?
True
What is the formula for a random variable?
The formula, if any, depends on the probability distribution function for the variable. In the case of a discrete variable, X, this defines the probability that X = x. For a continuous variable, the probability density function is a continuous function, f(x), such that Pr(a < X < b) is the area under the function f, between a and b (or the definite integral or f, with respect to x, between a and b.
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.
For a continuous random variable the probability that the value of x is greater than a given constant is?
The integral of the density function from the given point upwards.
Density function of a continuous random variable?
I am not quite sure what you are asking. If this answer is not complete, please be more specific. There are many probability density functions (pdf) of continuous variables, including the Normal, exponential, gamma, beta, log normal and Pareto. There are many links on the internet. I felt that the related link gives a very "common sense" approach to understanding pdf's and their relationship to probability of events. As explained in the video, a probability can be read directly from a discrete distribution (called a probability mass function) but in the case of a continuous variable, it is the area under the curve that represents probability.
What is the difference between a discrete and a continuous probability function?
A discrete random variable (RV) can only take a selected number of values whereas a continuous rv can take infinitely many.
