Let Xi, i=1, ,10, be independent random variables

In summary, independence of random variables means that there is no relationship or dependence between the outcomes of the variables. Unlike independent random variables, dependent random variables have a correlation between them. Independent random variables can have the same probability distribution, but there is no relationship between them. The notation "i=1, ,10" is commonly used to represent a sequence of variables in statistics and probability. Some real-world examples of independent random variables include the outcomes of a coin toss, medical test results, and stock prices.
  • #1
TomJerry
50
0
Let Xi, i=1,...,10, be independent random variables, each uniformly distributed over (0, 1). Calculate an approximation to P([tex]\sum[/tex]Xi > 6)
Solution

E(x) = 1/2
and
Var(X) = 1/12

[How should is calulate the approxmiate ]
 
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  • #2
Remember what the central limit theorem says about approximating sampling distributions of means if i.i.d random variables: you can also use it to obtain the sampling distribution of the sum of i.i.d random variables.
 
  • #3
Interestingly, Berry-Esseen gives [tex]p\approx 0.137 \pm 0.2[/tex] whereas the true error is closer to 0.002. Do any other theorems give more accurate error estimates?
 

Related to Let Xi, i=1, ,10, be independent random variables

What does it mean for random variables to be independent?

Independence of random variables means that the outcome of one variable does not affect the outcome of another. In other words, there is no relationship or dependence between the variables.

How are independent random variables different from dependent random variables?

Unlike independent random variables, dependent random variables have some kind of relationship or correlation between them. The outcome of one variable can affect the outcome of another.

Can independent random variables have the same probability distribution?

Yes, it is possible for independent random variables to have the same probability distribution. This means that the likelihood of each variable taking on a certain value is the same, but there is no relationship between the variables.

What is the significance of using "i=1, ,10" in the statement?

The notation "i=1, ,10" means that there are 10 independent random variables in the sequence, with each variable represented by a different subscript i. This notation is commonly used to represent a sequence of variables in statistics and probability.

What are some real-world examples of independent random variables?

Some examples of independent random variables in real life include the outcomes of a coin toss, the results of two separate medical tests, and the prices of different stocks in the stock market.

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