Significant change over NxM distributions

Cross Validated Asked on November 29, 2020

I have 100 sets of data, each of which consists of ~ 15 distributions along time, I’ve attached a figure of 1 of these sets to hopefully clear up what I mean. The plot shows the 95% confidence intervals and quartiles for each distribution, the red dot and line are actually irrelevant for this particular statistical test.

enter image description here

I want to determine for each of these sets whether or not between any two distributions, there is a significant difference. I originally considered the Kolmogorov Smirnov test, but for a reason I can’t remember now (which is frustrating me and I’m sure frustrating you too), that isn’t applicable. I’ve been considering the z test as outlined here: but i’m not sure if it is the best approach.

I also want to somehow be able to quantify the amount of sets of data across the 100 that contain significant difference, but not sure on how to do that yet (any ideas for that are most welcome).

Thank you very much

Add your own answers!

Related Questions

Cross validation and parameter tuning

5  Asked on November 20, 2020 by sana-sudheer


How does the Dyna Q algorithm works?

1  Asked on November 19, 2020 by nolw38


ReLU outperforming Softplus

1  Asked on November 12, 2020 by mike-land


Individual sampling weights and percentages

1  Asked on November 6, 2020 by seth-c


Bayesian Likelihood function range

1  Asked on October 29, 2020 by shamm


Zero inflated continuous outcome variables

0  Asked on October 26, 2020 by michaelkyei


How to test paired observations

1  Asked on October 23, 2020 by doug-fir


PCA loadings of correlation matrix

0  Asked on October 20, 2020 by mri


Ask a Question

Get help from others!

© 2022 All rights reserved. Sites we Love: PCI Database, MenuIva, UKBizDB, Menu Kuliner, Sharing RPP, SolveDir