Finding variance without knowing mean?

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The discussion revolves around a statistics problem where the variance needs to be calculated without knowing the mean. The given data includes the sample size (n=5), the sum of squares (Σx²=1320), and the sum of values (Σx=80). The poster deduces that the variance formula requires the mean to provide a numerical answer, which is not specified in the problem. They express concern that the teacher may expect a definitive answer rather than a function of the mean. The thread seeks insights on whether the problem can be solved with the provided information.
MadMike1986
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Hi,

my girlfriend is taking a business statistics class and she had a test today. she got stumped on a question and wrote it down so she could ask me about it when she got back since I'm pretty good at math. I tried solving it but from what i can tell it seems like you would need to know the mean in order to find the variance. the question is below:

Find the Variance:

n = 5
\Sigma x^{2} = 1320
\Sigmax = 80


I expanded out the variance formula. since we run from i=1 to n (where n=5)
I got the formula V = 1320 - 160u^{2} + 5u^{2}/5

where u = the mean.

My girlfriend says that the mean was not specified in the problem. I would have given my answer for the variance as a function of the mean as you can see above, but since this is a business statistics class i have the tendency to believe the teacher is expecting a numerical answer. Does anyone have any insight into how this problem can be solved, or is there not enough information given?

Thank you.
 
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note: in the variance formula that i expanded out, i meant for the entire numerator to be divided by 5. (n=5)
 
crap i just realized that i wasn't supposed to post this under here. i would delete it but i haven't figured out how yet. until i do i apologize.
 
The standard _A " operator" maps a Null Hypothesis Ho into a decision set { Do not reject:=1 and reject :=0}. In this sense ( HA)_A , makes no sense. Since H0, HA aren't exhaustive, can we find an alternative operator, _A' , so that ( H_A)_A' makes sense? Isn't Pearson Neyman related to this? Hope I'm making sense. Edit: I was motivated by a superficial similarity of the idea with double transposition of matrices M, with ## (M^{T})^{T}=M##, and just wanted to see if it made sense to talk...

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