Linear Regression
A statistical method that models the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data.
A statistical method that models the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data.
A statistical technique that uses several explanatory variables to predict the outcome of a response variable, extending simple linear regression to include multiple input variables.
A design approach that uses data, algorithms, and predictive analytics to anticipate user needs and behaviors, creating more personalized and effective experiences.
The use of statistical techniques and algorithms to analyze historical data and make predictions about future outcomes.
A design approach that predicts user needs and actions to deliver proactive and personalized experiences.
A statistical method used to predict a binary outcome based on prior observations, modeling the probability of an event as a function of independent variables.
The ability to identify and interpret patterns in data, often used in machine learning and cognitive psychology.
A recommendation system technique that makes predictions about user interests based on preferences from many users.
Also known as the 68-95-99.7 Rule, it states that for a normal distribution, nearly all data will fall within three standard deviations of the mean.