Non Central Chi Square distribution Assignment Help
11.11 Non Central Chi Square distribution:
The chi-square distribution defined as the sum of the squares of independent standard normal variates is often referred to as the central chi-square distribution. The distribution of the sum of the squares of independent normal variates each having unit variance but with possibly non zero means is known as non-central chi-square distribution. Thus if Xi, (i=1,2,…,n)are independent N(μi, 1), random variables then
Has the non central chi-square distribution with n degrees of freedom. Intuitively, this distribution would seem to depend upon the n parameters μ1, μ2,…….., μn but it will be seen that it depends on these parameters only through the non-centrality parameter.
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Following are some of the topics in Exact Sampling distributions in which we provide help:
- Exact Sampling distributions
- Derivation Of The Chi Square Distribution
- Moment Generating Function Of x2Distribution
- Cumulant Generating Function Of x2Distribution
- Limiting form of x2distribution for large degrees of freedom
- Characteristic function of x2distribution:
- Chi Square Probability Curve
- Conditions For The Validity Of Chi Square Test
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