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The variance of a random variable X is given by Var(x) = Eeilr; - p)? p where P, is the probability of a particular value x; and / is the mean of X. Suppose X is a...

Question

The variance of a random variable X is given by Var(x) = Eeilr; - p)? p where P, is the probability of a particular value x; and / is the mean of X. Suppose X is a random variable that takes the value of 0 with probability p ~Iwith P and 1 with P What is the variance of X?Select one:

The variance of a random variable X is given by Var(x) = Eeilr; - p)? p where P, is the probability of a particular value x; and / is the mean of X. Suppose X is a random variable that takes the value of 0 with probability p ~Iwith P and 1 with P What is the variance of X? Select one:



Answers

If the range of $X$ is the set \{0,1,2,3,4\} and $P(X=x)$ $=0.2,$ determine the mean and variance of the random variable.

And this question were given a variable X. With a discreet uniform distribution Access between zero and 99. We were asked to determine the me and the variance of X. So the mean, from our formula for a discreet uniform distribution is steve okay? For who, 99 over two days, 49.5 and the variance is the minus E plus one squared minus one over 12. So 99 0 plus one squared minus one over. Well, we'll give us 833 two. Fine. Do we have uh house, of course, for mean and experience?

It is important to get a solid foundation of the vocabulary for sampling distributions. For us to start this next part. Now, a sampling distribution is different than a sample distribution. So when we're talking about a sampling distribution, you're repeatedly taking samples out of a population with a specific size end and you're calculating some statistic about that sample. And then you're actually looking at the distribution of that statistic and how we can apply that later in our inferential statistics. So our first thing with vocabulary is that if we're looking at the probability distribution of all the possible values of the random variable X. Bar. Remember ex far as a sample mean? So I grab a sample and I find the mean of that sample. And then I grab another sample size, same size end, and I find the mean of that sample and I do that over and over and over. And then I look at the probability distribution of those um sample mean values. And that expert is calculated from a sample of size and from a population whose mean is new and whose standard deviation is sigma. That process produces a probability distribution known as the sampling distribution of exper.

Today we're going to solve a problem. Number seven here ffx Because to elect Scinto one minus X, the whole square zero does not. The context does not equal to one. Expectation is equal to into the 0 to 1 eggs in do to elect minus 24 X squared plus dual x cubed the X Well, Intel 0 to 1 ex clarity X minus 24 It was 0 to 1 picks cube. The yes do well in the 0 to 1 existed for the it's, which is equal to for execute 0 to 1 minus six Xs 24 0 to 1 plus well accessed. If I buy fight 0 to 1 but difficult to foreign toe. One cube minus four into zero Q minus 16 to 1 just before plus six into zero. Rested for plus you really do. One goes to fight by fight minus two Will in due the road is 25 by five, which comes to be by faith. Then we need to find ways and soft X variance off X is equal to the road to one eight square daughter to elect minus 24 X square plus well X cubed DX minus Dubai Side, the whole square. So which comes to be like well and 0 to 1 x cubed de Explain US 24 0 to 1. Access to for the X plus well, Intel 0 to 1. Access to fight the X minus four by 25 which is a call to three acceptable by existed for from 0 to 1, minus 24 access defied by five from 0 to 1 plus to exist to six 0 to 1, minus four by 25. So which comes to be like three minus zero, minus 24 by fight zero plus two minus zero minus four by 25 which is a kowtow won by 25 Expectation all fixes one way flight Parents off axis One day 25. Thank you.


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