I am en experimentalist and in most of my experiments I am interested in measuring the properties of distributions, i.e. the phenomenon I am measuring is stochastic and the parameters I am interested in are (in the simplest case) say the mean value and the width of the distribution (variance of standard distribution).(adsbygoogle = window.adsbygoogle || []).push({});

My "in" data is a times series wth n samples sampled at some frequency fs which is then post-processed in Matlab. If often deal with quite long time-series (millions of points) that take hours or days to aquire, and I am therefore interested in understanding how much here really is to gain my say doubling the number of aquired points.

My question is a practical one: how many samples do I need in order to estimate the shape of the distribution?

I know that the accuracy by which I can estimate the mean improves as √n, at least if one assumes a normal distribution.

But how quickly does the estimate of the std improve?

Also, can one say something about many samples one need to estimate the parameters for other common distributions (Poissonian etc)?

**Physics Forums - The Fusion of Science and Community**

Join Physics Forums Today!

The friendliest, high quality science and math community on the planet! Everyone who loves science is here!

The friendliest, high quality science and math community on the planet! Everyone who loves science is here!

# Estimating the standard deviation from sampled data

Loading...

Similar Threads for Estimating standard deviation | Date |
---|---|

Unbiased estimate of a parameter in the Rice distribution | Mar 29, 2018 |

A Error estimation in linear regression | Mar 12, 2018 |

I Why is the maximum likelihood estimation accurate? | Dec 20, 2017 |

Estimating the standard deviation | Sep 18, 2011 |

**Physics Forums - The Fusion of Science and Community**