How do you calculate the Grand Variance?

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To calculate the Grand Variance for the given data set, the correct formula is Grand Variance = SST / (N-1), where SST is the sum of squared differences from the grand mean and N is the total number of data points. Each group's variance must be adjusted for sample size, leading to a final calculation of 3.124 for the Grand Variance. It's crucial to avoid averaging the variances directly, as they involve different calculations due to their dependence on sample sizes. Understanding these concepts and using the appropriate formulas will yield the correct Grand Variance.
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Homework Statement



Im working on this data set, and I can't get the "Grand Variance" calculated correctly, driving me nutz!

So, its 3 groups of data.

Group 1 mean = 2.20
group 2 mean = 3.20
group 3 mean = 5

Group 1 variance = 1.70
Group 2 variance = 1.70
Group 3 variance = 2.50

Now, it asks what is the "Grand Variance"... The correct answer is 3.124 - but am not sure how the book got that value. I keep getting wrong :(

Any pointers?

Homework Equations


The Attempt at a Solution

 
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I hope you've been told at some time not to take an average of averages (unless you happen to know that the averages come from sample sets of the same size).
What else do you know about these groups? Their sizes perhaps?
 
haruspex said:
I hope you've been told at some time not to take an average of averages (unless you happen to know that the averages come from sample sets of the same size).
What else do you know about these groups? Their sizes perhaps?

5 people in each group...3 groups
 
Crap, I corrected my post!

It asks for the GRAND VARIANCE!, not grand mean. Grand Variance is 3.124
 
nukeman said:
It asks for the GRAND VARIANCE!, not grand mean. Grand Variance is 3.124
Same question would have arisen, so no harm done.
Think about the last step that would have been involved in calculating the mean of each group. What can you work backwards from the info you have to determine? Then do the same for the variances.
 
haruspex said:
Same question would have arisen, so no harm done.
Think about the last step that would have been involved in calculating the mean of each group. What can you work backwards from the info you have to determine? Then do the same for the variances.

All I did to get the Grand mean was calculate the mean, of the mean's of each group...
 
I keep getting wrong answer. I don't know what I am doing wrong. :(

Here is the data:

2ursg8g.png
 
nukeman said:
All I did to get the Grand mean was calculate the mean, of the mean's of each group...
Since the groups all happen to be the same size, that should be fine (but I hope you would not have done that otherwise). And you get 3.467, right?
But you can't do that with the variances because the formula used there has an n/(n-1) term, where n is the number of data values. So for each group that gives 5/4, but for the grand variance it will be 15/14.
Have you tried to calculate the group variances yourself? Do you get the values in the table?
 
Hi nukeman! :smile:

The grand variance is
$$\text{Grand Variance} = {SST \over N-1}$$
where:
##SST## is the sum of the squared differences of each score with the grand mean,
##N## is the total number of scores (15 in your case).​
If you want, you can also calculate it without using the actual scores.
But then you'll need a couple of additional formulas, so you can calculate SST differently.
Do you have formulas for that?
 
  • #10
Hey "I Like Serena"

I don't quite understand the SST part of that equation.

Do I take the squared differences of ALL 15 data points, then add them up?

then divide by n-1 ? (14) ?
 
  • #11
Yes.
 
  • #12
I like Serena said:
Yes.

ahhg I did that! Don't tell me I just messed up on my calculator and that's why I am trying all these different things! lol :)
 
  • #13
So are you good now?
 
  • #14
Oh yes, I got it! Thanks!

While you are here, your formula make more sense than the one I was given. What is the formula for the Grand SD?

I just square root the Grand Variance correct?
 
  • #15
Correct.
 
  • #16
If you're interested, here are a couple of other identities (##n=5##).
They come from (one-way) ANOVA theory which is what you are doing.

$$SST = SSM + SSE$$
$$SSM=n((\bar X_1 - \text{Grand Mean})^2 + (\bar X_2 - \text{Grand Mean})^2 + (\bar X_3 - \text{Grand Mean})^2)$$
$$SSE=(n-1)(s_1^2 + s_2^2 + s_3^2)$$
 
  • #17
Wow, thanks! Appreciate it.
 
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