Is it possible to find the SD without the data?

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In summary, the conversation discusses finding the standard deviation (SD) from the mean and a value at a specific percentile (99th percentile). It is mentioned that the shape of the distribution needs to be known, and if it is normal, the SD can be calculated using the value for a when aσ = .99. It is suggested to check this calculation. The conversation also mentions using the invNorm function to find the SD, with a value of 0.36 being a good fit. This results in an estimated value of 4.26 for the 90th percentile.
  • #1
stonecoldgen
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I have the mean and I have the value at a percentile (99th percentile to be specific). I am just wondering if it's possible to find the SD. Actually, what I am trying to find is the value at the 90th percentile (I think I need the SD to do it, but maybe just maybe there's another method...)


Just in case, the mean is 3.8 and the value at the 99th percentile is 4.64
 
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  • #2
You need to know the shape of the distribution. If it is normal you can get the S.D. (σ)from the data given by looking up the value for a when aσ = .99. I get a ≈ 2.33, but I suggest you check it. σ = (4.64 - 3.8)/2.33.
 
  • #3
Oh yeah, I forgot to say it's a normal distribution. I used the invNorm function to see which standard deviation best models the situation, so I found out that 0.36 does it pretty well. So the value I got for the 90th percentile is more of an estimate (4.26), but I think it fits well enough.
 

Related to Is it possible to find the SD without the data?

1. Can the standard deviation (SD) be calculated without having the data?

No, it is not possible to find the SD without the data. The SD is a measure of the spread of a set of data points around the mean, and it is calculated using the actual data values. Without the data, there is no way to determine the variability and calculate the SD.

2. Is there an alternative method to estimate the SD without the data?

There are some statistical techniques that can be used to estimate the SD without having the data, such as bootstrapping or using a sample SD to estimate the population SD. However, these methods may not be as accurate as calculating the SD from the actual data points.

3. Is it necessary to have the complete data set to find the SD?

Yes, the complete data set is required to accurately calculate the SD. If any data points are missing, it can affect the overall variability and thus, the SD. It is important to have all the data points to get an accurate measure of the spread of the data.

4. Can the SD be approximated using other measures of variability?

Yes, there are other measures of variability, such as the range or interquartile range, that can be used to estimate the SD. However, these measures may not provide an accurate representation of the spread of the data, and it is recommended to use the SD for its robustness and sensitivity to outliers.

5. How does the amount of data affect the accuracy of the SD?

Generally, the more data points you have, the more accurate the SD will be. As the sample size increases, the SD becomes a better estimate of the population SD. However, even with a small sample size, the SD can still provide valuable information about the variability of the data.

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