Statistics - Standard Deviation, Standard Error and Mean

In summary, the conversation discusses calculating the average of 4 numbers from a data set of 6 numbers in Excel without manually selecting the 4 numbers. The suggestion is to use "robust" estimates such as the median and the median absolute deviation to better account for distributions with outliers or non-symmetrical shapes. Other suggestions include using dot plots or stemplots to represent the data.
  • #1
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Hello,

Just had a question regarding statistical analysis.

I'm trying to calculate the average of 4 numbers from a data set of 6 numbers in excel without manually choosing to average only the 4 numbers.

e.g.


85 20 32 45 27 3 (total mean = 35.3 desired mean = 31)
100 30 27 40 21 1
...etc

The middle 4 numbers represent a more realistic result whilst the two end numbers are irrelevant.

I've tried looking into weighted averages however I'm unsure how to apply this to an excel sheet.

I'd prefer to find a formula which would discount numbers which vary wildly from the average amount and focus only on the few that don't.

Any help would be greatly appreciated.
 
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  • #2
You have six numbers - if you picked four of them at random, what would be their average?
That about it?

Clearly that depends on the four numbers - but you can work out each possible combination of 4, and work out the average for each one. The expectation value of the averages will be your answer.
 
  • #3
A better strategy than excluding observations arbitrarily would be to compute "robust" estimates of the distribution, e.g. the median instead of the mean and the median absolute deviation (MAD) as an estimator for the variability.
See
http://en.wikipedia.org/wiki/Robust_statistics
 
  • #4
As a general comment, to reinfoce what was already said, in distributions that are not symmetrical or not unimodal, and or distributions with outliers, the variance is not a good measure of spread. You may also want to represent your data with a dot plot or stemplot:

http://en.wikipedia.org/wiki/Stem-and-leaf_plot
 
  • #5


Hello,

Thank you for your question about statistical analysis. To calculate the average of only 4 numbers from a data set of 6, you can use the AVERAGEIF function in Excel. This function allows you to specify a criteria for which numbers to include in the average calculation. In this case, you can use the criteria "greater than 10" to exclude the two end numbers that are irrelevant. The formula would look like this: =AVERAGEIF(A1:A6,">10"). This will give you the average of the four numbers in the range A1:A6 that are greater than 10.

In terms of discounting numbers that vary wildly from the average, you can use the standard deviation and standard error to determine the amount of variation in the data set. The standard deviation measures the spread of the data points from the mean, while the standard error measures the accuracy of the mean. If you have a large standard deviation and a small standard error, it may indicate that there are outliers in the data that are affecting the average. In this case, you may want to consider removing those outliers or using a different measure of central tendency, such as the median.

I hope this helps and please let me know if you have any further questions. Best of luck with your analysis!
 

1. What is the difference between standard deviation and standard error?

Standard deviation is a measure of how much the data values in a sample vary from the mean. It is calculated by taking the square root of the variance. On the other hand, standard error is a measure of how much the sample mean is likely to differ from the true population mean. It is calculated by dividing the standard deviation by the square root of the sample size.

2. How is standard deviation used in statistics?

Standard deviation is used to measure the spread or variability of a set of data values. It helps to understand how much the data values deviate from the mean or average. It is also used to calculate the confidence intervals and make inferences about the population based on the sample data.

3. What is the relationship between standard deviation and mean?

Standard deviation and mean are two measures of central tendency in a data set. While mean represents the average value of the data, standard deviation measures how much the data values deviate from the mean. A higher standard deviation indicates a larger spread of data values, while a lower standard deviation indicates a smaller spread.

4. How is standard error calculated?

Standard error is calculated by dividing the standard deviation by the square root of the sample size. It is represented by the symbol "SE" and is often used to estimate the standard deviation of the population mean.

5. Can standard error be used to make predictions about the population?

Yes, standard error can be used to make predictions about the population. It is often used to calculate confidence intervals, which help in making inferences about the population mean based on the sample data. However, it should be noted that the accuracy of these predictions depends on the sample size and the variability of the data.

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