Standard deviation of series of trials

In summary, we have two methods for sawing ten planks, one that saws them all at once resulting in uniform length and one that saws them individually. Both methods have an expected value of 1 meter and a standard deviation of 0.005 meters. We are trying to find the standard deviation of both methods and are given a random variable X. We can calculate SD(10X) and SD(X1 + X2 + ... + X10) using the formula SD(A + B + ... + Z) = sqrt(SD(A)^2 + SD(B)^2 + ... + SD(Z)^2). This formula shows that the variance of a sum of random variables is equal to the sum of their variances. By
  • #1
Gauss M.D.
153
1
Say we want to saw ten planks and we have two methods available - one is sawing them all at once, ensuring they're all exactly uniform length. The other method is sawing them individually. Either method has EV of 1m and a standard deviation of 0.005m. I want to find the standard deviation of both methods.

In other words, given a random variable X, I guess what we're trying to figure out is SD(10X) and SD(X1 + X2 + ... + X10).

I'm not sure how to calculate the second one. Anyone want to give me a push? :S
 
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  • #2
[tex]\operatorname{SD}(A + B + \cdots + Z) = \sqrt{\operatorname{SD}(A)^2 + \operatorname{SD}(B)^2 + \cdots + \operatorname{SD}(Z)^2}[/tex]

What this basically says is that the variance Var(X) = SD(X)² is linear:
[tex]\operatorname{Var}(A + B + \cdots + Z) = \operatorname{Var}(A) + \operatorname{Var}(B) + \cdots + \operatorname{Var}(Z)[/tex]

Also note that by setting A = B = ... = X you can actually derive the result for SD(10X).
 
  • #3
Thanks a ton!
 

FAQ: Standard deviation of series of trials

1. What is the definition of standard deviation?

The standard deviation is a measure of how spread out a series of values is from the mean, or average, of the series. It tells us how much the individual values deviate from the average and gives us an idea of the variability or uncertainty in the data.

2. How is standard deviation calculated?

To calculate the standard deviation of a series of trials, you first need to find the mean of the series by adding all the values and dividing by the number of trials. Then, for each individual value, subtract the mean and square the result. Next, add up all the squared differences and divide by the number of trials. Finally, take the square root of this value to get the standard deviation.

3. What does a high standard deviation indicate?

A high standard deviation indicates that the values in the series are spread out from the mean. This means that there is a lot of variability or uncertainty in the data, and the individual values may be far from the average. In other words, the data points are more diverse and may not be as reliable or consistent.

4. How does sample size affect standard deviation?

The larger the sample size, the more reliable and accurate the standard deviation will be. This is because a larger sample size provides more data points and reduces the impact of outliers or extreme values. In general, a larger sample size will result in a smaller standard deviation, as the data points are more likely to be closer to the mean.

5. Can standard deviation be negative?

No, standard deviation cannot be negative. It is always a positive value, as it is a measure of distance from the mean. A value of zero indicates that all the data points are equal to the mean, while a larger value indicates more variability from the mean. Therefore, standard deviation can never be negative.

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