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In statistics, distribution of sampling means is known as the standard error. Standard error estimates how accurate the mean of any given sample represents the true mean of the population. Standard increases when standard deviation increases. It decreases when the sample size increases because more data yields less variation in the results.
A large standard error indicates that the means are spread out and the sample mean is not likely to be a true reflection of the true population mean. A smaller standard error indicates the means are closer together and it is more likely that the sample means is an accurate representation of the true population mean.
The formula for the standard error is as follows:-
I have written a function to calculate the standard error of a list. This function is part of a Jupyter Notebook of statistical functions I have written, and can be found here:- https://colab.research.google.com/drive/18UF3voMAoVpBx1G4wLX7WqFsUwhk2sGd?usp=sharing
The psuedocode for the function I have written to calculate the standard error is as follows:-
- Define the function…
