| Basic Probability and Statistics | ||
| • GAIA parallaxes | (blank) | |
| • Probability and conditional probability | ||
| • Estimators | (blank) | (filled) |
| • Uncertainties, covariance, and correlation | (blank) | (filled) |
| Random numbers, data simulation, and some numerical methods | ||
| • Pseudo-random deviates | (blank) | (filled) |
| • Data simulation and convolution | (blank) | (filled) |
| • Cross-correlation | (blank) | (filled) |
| Statistical Interference | ||
| • Likelihood | (blank) | (filled) |
| • Linear Least Squares | (blank) | (filled) |
| • Non-linear Least Squares | (blank) | (filled) |
| • Multivariate fits | (blank) | (filled) |
| • Fitting uncertainties | (blank) | (filled) |
| • Minimization | (blank) | (filled) |
| • Model comparison | (blank) | (filled) |
| • Markov Chain Monte Carlo | (blank) | (filled) |
| • MCMC and density estimation | (blank) | (filled) |
| • Density estimation and clustering | (blank) | (filled) |
| • Principal component analysis | (blank) | (filled) |
| • Manifold learning | (blank) | |
| • Neural networks | (blank) | (filled) |