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Does the probability that a continuous random variable take a specific value depend on the probability density function?
Wiki User
∙ 10y ago
No. The probability that a continuous random variable takes a specific value is always zero.
Wiki User
∙ 10y ago
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Is the normal probability distribution applied to a continuous random variable?
Yes.
What is the probability the random variable will assume a value between 40 and 60?
It depends on what the random variable is, what its domain is, what its probability distribution function is. The probability that a randomly selected random variable has a value between 40 and 60 is probably quite close to zero.
What is the probability of scoring 115 when mean is 100 and standard deviation is 15?
The probability of scoring an exact value for a continuous variable is zero for any value. The probability of scoring 115 (or more) is 15.87%
Is height of human beings discrete variable or continuous variable?
It is a continuous variable.
Is intelligence a continuous variable?
yes
What is probability mass function?
It is a function which is usually used with continuous distributions, to give the probability associated with different values of the variable.
What is the probability that a continuous random variable takes on a specific value?
Zero.
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.
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 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.
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.
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.
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.
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.
What are the 4 probabilities?
There are not just 4 probabilities. Probability is a continuous variable ranging from 0 to 1: it can take infinitely many values.There are not just 4 probabilities. Probability is a continuous variable ranging from 0 to 1: it can take infinitely many values.There are not just 4 probabilities. Probability is a continuous variable ranging from 0 to 1: it can take infinitely many values.There are not just 4 probabilities. Probability is a continuous variable ranging from 0 to 1: it can take infinitely many values.
In Excel what function will give you an estimate of the value of a continuous random variable if you know the probability of that variable?
There are infinitely many continuous probability functions and there is no information whatsoever in the question to determine the nature of the distribution: uniform, Normal, Student's t, Chi-square, Fisher's F, Gamma, Beta, Lognormal, etc, etc. Second, every continuous function must have at least two points for which the probability is the same. There is no information as to which of these two (or more) points is the relevant one. There can therefore be no answer.
