These are exploratory work done when taking the Statistics course (2018-19 University of Birmingham Dr Guy Davies). The exploration includes:
(Assuming there are two uncorrelated distributions with means = μ_1, μ_2; and standard deviations = σ_1, σ_2)
- Verifying the additive rule (new mean = μ_1 + μ_2 with new std = sqrt(σ_1^2 + σ_2^2))
- Verifying the multiplicative rule
- Verifying raising the distribution to the n-th power will follow the rules specified in the lecture
- Verifying that general error propagation formula works
These explorations above are all plotted and saved as png.
Other .py files in this repo attempts to look deeper into the nature of covariance and form an intuitive understanding about it; but it failed to do so. For a more successful attempt please look at my Covariance repository.