Random Variables and mathematical expectations

Probability which explains x is equal to or less than particular value is classified as

• Cumulative Probability

• Continuous Probability

• Marginal Probability

• Discrete Probability

A variable that can assume any possible value between two points is called

• Discrete random variable

• Discrete Sample Space

• Continuous random variable

• Random Variable

If c is constant ,then E(c) is

• 1

• c f (c)

• 0

• c

E[X-E(X)] is equal to

• V(X)

• 0

• E(X)-X

• E(X)

If the random variable takes negative values ,then the negative values will have

• negative Probabilities

• Constant Probabilities

• Positive Probabilities

• Difficult to tell

A Discrete probability distribution may be represented by

• Table

• Mathematical Equation

• Graph

In a discrete probability distribution the sum of all the Probabilities is always equal to

The distribution function F(x) is equal to

• P(X=x)

• P(X $\le$ x)

• P(X $\ge$ x)

• All of these

The height of persons in a country is a random variable of the type

• Continuous random variable

• Discrete random variable

• Both (a) and (b)

• Neither (a)nor (b)

An expected value of a random variable is equal to it's