which of the following is not a property of the sampling distribution of the variance?

Sophia Jennifer S


The sampling distribution of the variance refers to the distribution of variances of iid random variables.

The distribution of the variance of a random variable is the distribution of the squares of the variances of iid random variables. But the variance of a random variable depends on the mean value.

The distribution of the variance of a random variable is related to the distribution of the mean value. The distribution of the variance of a random variable is a bell-shaped curve. The higher the variance, the wider the bell.

The distribution of the variance of a random variable is a bell-shaped curve. The higher the variance, the wider the bell. In statistics, the distribution of the variance of a random variable is called the standard deviation.

The distribution of the variance of a random variable is a bell-shaped curve. The higher the variance, the wider the bell. The lower the variance, the wider the bell. The distribution of the variance of a random variable is a bell-shaped curve. The higher the variance, the wider the bell. The distribution of the variance of a random variable is a bell-shaped curve. The higher the variance, the wider the bell. The higher the variance, the wider the bell.

To get a sense of the variance of a random variable, we’ll look at the distribution of the variance of the variable and then we’ll look at the distribution of the variance of the variable. If the variables are all equally distributed, the variance of the variable is proportional to the difference between the values of the variables. So, the distribution of the variance of a variable is proportional to the difference between the values of the variances.

If the distributions of the variance of a random variable are all equally spread out, then the variance of the random variable is proportional to the sum of the variances. So, if the distributions of the variances of the random variables are all equally spread out, then the variance of the random variable is proportional to the sum of the values of the random variables.

The problem with the above statement is that because the random variables are random, the variance of a random variable will be a random variable. So, the variance of a random variable is not proportional to the sum of the values of the random variables. The variance of a random variable is a random variable.


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