PROBIT Meaning and
Definition
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Probit refers to a statistical method used in econometrics and other fields for estimating the relationship between a binary response variable and a set of explanatory variables. The term "probit" combines the words "probability" and "unit." The probit model assumes that the binary response variable follows a standard normal distribution, and the relationship between the explanatory variables and the response variable is described through the cumulative distribution function of the standard normal distribution.
In the probit model, the probability that the binary response variable takes the value of 1 (success) is estimated based on a linear combination of explanatory variables. This linear combination is then transformed through the inverse cumulative distribution function of the standard normal distribution, known as the probit function, to obtain the estimated probability. The probit model is often preferred over other models, such as the logistic regression model, when the normal distribution is a reasonable assumption for the error term.
The estimation of the probit model involves maximum likelihood estimation, where the likelihood function represents the probability of observing the data given the model parameters. The maximum likelihood estimates provide information on the significance and direction of the explanatory variables' impact on the probability of success. Probit analysis is commonly used in various disciplines, such as economics, sociology, psychology, and epidemiology, where the focus is on modeling and analyzing binary response variables.
Common Misspellings for PROBIT
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