Show how the variance decrease as degrees of freedom/sample size get bigger

In summary, the conversation is about finding the variance of (n-1)s2/σ2 and how it results in larger variances instead of smaller. The question asks if a chart should be used and the speaker mentions a Chi-squared distribution with (n-1) degrees of freedom. The responder asks if the variance formula for the Chi-squared distribution is known.
  • #1
rogo0034
37
0

Homework Statement


TNtoZ.png



Homework Equations



XY0kG.png


The Attempt at a Solution



I'm confused actually how to go about this. Sounds very simple, but when i do what they suggest, 'first, find the variance of (n-1)s22

i get larger variances rather than smaller, which makes no sense. should i be using the chart for this? (below)

uhT2u.png
 
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  • #2
rogo0034 said:

Homework Statement


TNtoZ.png



Homework Equations



XY0kG.png


The Attempt at a Solution



I'm confused actually how to go about this. Sounds very simple, but when i do what they suggest, 'first, find the variance of (n-1)s22

i get larger variances rather than smaller, which makes no sense. should i be using the chart for this? (below)

uhT2u.png

Since you don't tell us what the chart represents, it is impossible to tell if it is relevant or not; I suspect not.

You are told that [itex] V = (n-1)S^2/\sigma^2 [/itex] has a Chi-squared distribution with (n-1) degrees of freedom. Do you know the variance formula for the Chi-squared distribution? (It is readily available.)

RGV
 

1. How does increasing degrees of freedom affect the variance?

As the degrees of freedom increase, the variance decreases. This means that there is less variability in the data and the values are becoming more consistent.

2. Does the sample size affect the decrease in variance?

Yes, as the sample size increases, the variance also decreases. This is because a larger sample size provides more data points, resulting in a more accurate representation of the population.

3. Is there a limit to how much the variance can decrease with increasing degrees of freedom and sample size?

Yes, there is a limit to how much the variance can decrease. As the sample size and degrees of freedom approach infinity, the variance will approach a minimum value known as the population variance.

4. Why is it important to consider degrees of freedom when analyzing data?

Degrees of freedom take into account the number of independent pieces of information in a dataset. It is important to consider this when analyzing data because it affects the reliability and accuracy of statistical tests and conclusions drawn from the data.

5. Can the variance ever increase with increasing degrees of freedom and sample size?

No, the variance will always decrease with increasing degrees of freedom and sample size. This is because as more data is collected, the values become more consistent and the variability decreases.

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