Standard deviation of a new sample

In summary, the conversation discusses the calculation of standard deviation for a subset of resistors with a mean of 100 ohms and a standard deviation of 5 ohms, while the original set has a mean of 100 ohms and a standard deviation of 20 ohms. The question does not specify the number of resistors in the original set, but it is assumed that the standard deviation of the remaining sample would be greater than 20 ohms due to the removal of resistors closest to the mean. The solution involves knowing the total number of resistors and the number in the subset.
  • #1
seidjeep
1
0
Hello all,

I am trying to figure out the following question with no luck: I have a box of resistors, mean 100 ohms and SD of 20 ohms. I form a subgroup of these resistors with mean of 100 ohms and SD of 5 ohms. Find the standard deviation of the remaining sample. The question does not give starting number of resistors. I'm guessing the standard deviation would be greater than the original 20 ohms since we removed all the resistors closest to the mean. Any clues about how to get this started would be awesome. Thanks.
 
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  • #2
The key to this is knowing how many in the original set and how many have been set aside into the subset. It would be a straightforward calculation as a function of these parameters.
 

What is standard deviation?

The standard deviation is a measure of how much the data values deviate or vary from the average or mean value. It is a commonly used measure of the spread or variability of a set of data.

How is standard deviation calculated?

To calculate the standard deviation of a sample, you need to first find the mean (average) of the data. Then, for each data point, subtract the mean and square the result. Next, add all of these squared differences together. Finally, divide this sum by the number of data points minus one, and take the square root of the result. This gives you the standard deviation of the sample.

Why is standard deviation important?

Standard deviation is important because it helps us understand the variability of a data set. It allows us to see how spread out the data values are from the mean and can help us identify outliers or unusual values. It is also used in many statistical analyses and can help us make more accurate predictions based on the data.

What does a high or low standard deviation indicate?

A high standard deviation indicates that the data values are spread out from the mean, meaning there is a lot of variability in the data. A low standard deviation indicates that the data values are close to the mean, meaning there is less variability in the data.

How does sample size affect the standard deviation?

The larger the sample size, the more precise the standard deviation will be. This is because a larger sample size provides more data points and a better representation of the population. A smaller sample size may result in a less accurate estimate of the population's standard deviation.

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