| Bayes’ Theorem | Uses prior knowledge to calculate the probability of an event given new evidence |
| Markov Chains | A sequence of possible events, where the probability of each event depends only on the state attained in the previous event |
| Monte Carlo Simulation | Uses repeated random sampling to estimate statistical properties of some phenomenon |
| Poisson Process | Models the number of times certain events occur within a specified interval of time or space |
| Naive Bayes Classifier | Assumes independent predictors and calculates the probability of a class based on the presence of various predictors |
| Maximum Likelihood Estimation | Estimates the parameters of a statistical model by maximising the likelihood function |
| Gaussian Mixture Models | Represents a composite distribution whereby points are drawn from one of several Gaussian sub-distributions, each specified by their mean and covariance |
| Bernoulli Process | Special type of a Poisson process where the time between two events follows an exponential distribution |
| Expectation-Maximization | An iterative method to find maximum likelihood or maximum a posteriori estimates of parameters in statistical models |
| Hidden Markov Model | Assumes the Markov property to model hidden states |
| Machine Learning Algorithms using Probability | They apply probability and statistical concepts to predict the outcome |
| Bayesian Networks | Represents a set of variables and their conditional dependencies via a directed acyclic graph |
| Conditional Random Fields | Used in machine learning to predict a sequence of states given a sequence of observations |
| Logistic Regression | Estimates parameters of a logistic model and thereby predicting the probability of occurrence of an event |
| Normal Distribution | A probability function that describes how the values of a variable are distributed |
| Kernel Density Estimation | A non-parametric way of estimating the probability density function of a random variable |
| Chi Square Test | Assess two types of comparison: tests of independence and goodness of fit |
| Fisher’s exact test | Finds statistical significance in a 2×2 contingency table |
| Information Gain & Entropy | Determine the best attribute for ID3 decision tree algorithm |
| Student’s T-test | Estimates whether the means of two groups are statistically different from each other |
