The total area under the density curve for a continuous random variable must equal 1. Given that the area from 0 to 5 is 0.00625, the area from 5 to 800 can be calculated by subtracting this value from 1. Therefore, the area under the density curve from 5 to 800 is (1 - 0.00625 = 0.99375).
True
Yes. It is a continuous variable. As used in probability theory, it is an example of a continuous random variable.
The integral of the density function from the given point upwards.
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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.
No. The probability that a continuous random variable takes a specific value is always zero.
It is a discrete random variable.
True
Yes. It is a continuous variable. As used in probability theory, it is an example of a continuous random variable.
continuous random variable
The integral of the density function from the given point upwards.
Usually we consider a random variable which assigns a value to the outcome of an event. The value assigned to the outcome can be either discrete or continuous. The continuous random variable is a random variable whose domain is defined over a continuous range. Examples: Daily inches of rain, speed of cars on highway, purchases made everyday at grocery stores.
it is a continuous random variable
Yes.
Zero.
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.
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