- #1
nomadreid
Gold Member
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chi-squared dist. converges to normal as df goes to infinity, but...
This is surely going to sound naive, but at least this will make it easy to answer.
For a chi-squared distribution, if k = the degrees of freedom, then
[a] k = μ = (1/2) σ2
as k goes to infinity, the distribution approaches a normal distribution.
But when I put these two together, I get
[c] as k goes to infinity, the mean and the variance become infinite
which would seem odd for a normal curve.
What am I getting wrong here? Thanks in advance.
This is surely going to sound naive, but at least this will make it easy to answer.
For a chi-squared distribution, if k = the degrees of freedom, then
[a] k = μ = (1/2) σ2
as k goes to infinity, the distribution approaches a normal distribution.
But when I put these two together, I get
[c] as k goes to infinity, the mean and the variance become infinite
which would seem odd for a normal curve.
What am I getting wrong here? Thanks in advance.