Calculating std and 95% confidence intervals in a 3d matrix along the 3rd dimension

6 次查看（过去 30 天）
Laila Rida
Laila Rida 2021-4-4
回答： Aditya Patil 2021-4-7
My data is organized in a 3d matrix (subjects x conditions x regions of interest). I've collapsed (averaged) across subjects and conditions so that I'm left with one value for each region of interest using mean(mean(M(:, :, :))). However, I'm trying to find the std and 95% confidence interval (to help with visualization) and I'm not sure if it is statistically sound to use the same logic to calculate the std (i.e. std(std(M(:, :, :))). And, when calculating the 95% CI, which dimension should I use to decide my sample size?

请先登录，再回答此问题。

回答（1 个）

Aditya Patil
Aditya Patil 2021-4-7
std(std(M)) would give you std deviations of the std deviations, which I assume is not what you are expecting. If you want std deviations along a specific axis, use the following syntax
std(M,w,dim)
See Standard Deviation Along Matrix Rows for an example.
Alternately, if you want std deviation across all values, do
std(M,w,'all')

类别

在 Help Center 和 File Exchange 中查找有关 Descriptive Statistics and Visualization 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by