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What is Expected Value of a random variable?
The expected value of a variable is its long-run average value of the repetitions of the number of experiment it represents. For example, the expected value of a dice roll is 3.5, which is, a rough average of an extremely large number of dice rolls is always nearly equal to 3.5. The law of large numbers states that the arithmetic mean of the values mostly converges to the expected value as the number of repetitions goes to infinity. The expected value is also known as EV, mathematical expectation, first moment or mean.
What is Variance of a random variable?
In statistics and probability theory, variance measures how far a set of numbers can be spread out. A variance of zero indicates that all the values are identical. Variance is always non-negative. A small variance indicates that the data points tend to be very close to the expected value and hence close to each other as well. A high variance indicates that the data points are quite spread out around the mean and also from each other.
The concept of expected value and variance is easy to understand with graphs and examples. You can find such solutions in our Expected value and Variance of a random variable Homework help. The concept is completely statistics based and a little difference in understanding may lead to in numerous mistakes. With our brilliant guidance, you can clear your concept. Our expert guidance will help you clear your doubts.
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