Notations --------------- This page was inspired from the following `Wikipedia page `_. Sample and Population ===================== A *population* is the entire population that you want to analyze. It is a exhaustive set. A *sample* is a subset of the population. It is a non-exhaustive set. .. figure:: figures/population_sample.svg :align: center :width: 300px *Inferential statistics* allows you draw conclusions (with a certain degree of confidence) on a population using samples. A Tale of Schizophrenia ================================ Two different notation conventions are used. The one to use depends if you are working on a *population* or a *sample*: .. list-table:: Notation :align: center :header-rows: 1 * - Metric - Population - Sample - Notes * - Sample mean - :math:`\mu` - :math:`\overline{x}` - * - Variance - :math:`\sigma^2` - :math:`s^2` - :math:`s^2_n` without `Bessel's Correction `__ * - Standard deviation - :math:`\sigma` - :math:`s` - :math:`s_n` without `Bessel's Correction `__ To determine the metric of a population (say :math:`\mu`) using a sample, we use an estimator. In the case of :math:`\mu`, we use :math:`\overline{x}` as an estimator. .. note:: Estimators can also be denoted with the hat symbol. For example :math:`\hat{\mu}\equiv\overline{x}`. Operators ========== Expected value ^^^^^^^^^^^^^^^ The expected value (*espérance*) of a random variable :math:`X` is noted :math:`\mathbb{E}[X]`. It as the following linearity properties: .. math:: \mathbb{E}[X+Y]=\mathbb{E}[X] + \mathbb{E}[Y] .. math:: \mathbb{E}[\alpha X]=\alpha\mathbb{E}[X] Variance ^^^^^^^^ The variance operator of a random variable :math:`X` is noted :math:`\mathbb{V}[X]` or :math:`\mathrm{Var}[X]`. Coraviance ^^^^^^^^^^ The covariance operator of a random variable :math:`X` and :math:`Y` is noted :math:`\mathrm{Cov}[X,Y]`.