Solve the variance problem below - statistics

In summary, the conversation is about a question regarding the variance equation and the poster is seeking for a quicker approach. Mark provides a proof for a shortcut using summations and the fact that the sum of x is equal to N times the mean of x. The poster confirms understanding and thanks Mark for clarifying.
  • #1
chwala
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Homework Statement
see attached
Relevant Equations
variance
The question is below:

1635595952630.png


below is my own working;
1635596053833.png
the mark scheme for the question is below here;
1635596099561.png


i am seeking for any other approach that may be there...am now trying to refresh on stats...bingo!
 
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  • #2
chwala said:
Homework Statement:: see attached
Relevant Equations:: variance

The question is below:

View attachment 291394

below is my own working;
View attachment 291395the mark scheme for the question is below here;
View attachment 291396

i am seeking for any other approach that may be there...am now trying to refresh on stats...bingo!
Here's a quicker way:
##\sum (x - \bar x)^2 = \sum x^2 - N \cdot \bar x^2##

Proof:
##\sum (x - \bar x)^2 = \sum(x^2 - 2x\cdot \bar x + \bar x^2) ##
##= \sum x^2 - 2\cdot \bar x \sum x + \sum \bar x^2 = \sum x^2 - 2\bar x \cdot N \cdot \bar x + N \bar x^2 = \sum x^2 - N \cdot \bar x^2##
All summations are from n = 1 to N.
In the proof above, I'm using the fact that ##\sum x = N \bar x##
 
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  • #3
Is the proof missing something...I will counter check it later...
 
  • #4
I just had a look at your proof...thanks Mark...I wasn't certain on the last part of your equation involving the mean. Its now clear to me from my study (shown below). Bingo!

1635679616725.png
 
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  • #5
chwala said:
I just had a look at your proof...thanks Mark...I wasn't certain on the last part of your equation involving the mean. Its now clear to me from my study. Bingo!
Yes, that's it. I've edited my post to change 'n' to 'N', which I hope makes it clearer.
 

FAQ: Solve the variance problem below - statistics

What is variance in statistics?

Variance is a measure of how spread out a set of data points are from the mean or average. It is calculated by taking the average of the squared differences between each data point and the mean.

How is variance different from standard deviation?

Variance and standard deviation are both measures of spread in a set of data, but variance is calculated by squaring the differences from the mean, while standard deviation is calculated by taking the square root of the variance. Standard deviation is a more commonly used measure as it is in the same units as the original data.

How do you solve for variance?

To solve for variance, you need to follow these steps: 1. Calculate the mean of the data set. 2. Subtract the mean from each data point. 3. Square each of the differences. 4. Find the average of the squared differences. This is the variance.

What is the purpose of calculating variance?

Calculating variance allows us to understand how spread out a set of data is and how much the data points deviate from the mean. It is a useful tool in comparing data sets and determining the reliability of the data.

How is variance used in statistical analysis?

Variance is used in statistical analysis to measure the variability of a data set and to make comparisons between different data sets. It is also used in other statistical calculations, such as calculating the standard deviation and determining the significance of differences between groups in an experiment.

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