If you sum enough Gaussians you can get close to any distribution you want. I’m not sure what the information behind “it’s Gaussian” in this context. (It clearly doesn’t look like a mixture of a few Gaussians...)
It clearly doesn’t look like a mixture of a few Gaussians
It does to me. If their means are close enough compared to their variances, it’ll look like a unimodal distribution. For a good example, a student t distribution is a mixture of gaussians with the same mean and variances differing in a certain way, and it looks exactly like these images.
If you sum enough Gaussians you can get close to any distribution you want. I’m not sure what the information behind “it’s Gaussian” in this context. (It clearly doesn’t look like a mixture of a few Gaussians...)
It does to me. If their means are close enough compared to their variances, it’ll look like a unimodal distribution. For a good example, a student t distribution is a mixture of gaussians with the same mean and variances differing in a certain way, and it looks exactly like these images.
See the first image here: https://en.m.wikipedia.org/wiki/Student’s_t-distribution