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High Quality Content by WIKIPEDIA articles! In probability theory and statistics, the probit function is the inverse cumulative distribution function (CDF), or quantile function associated with the standard normal distribution. It has applications in exploratory statistical graphics and specialized regression modeling of binary response variables. For the standard normal distribution (often denoted N(0,1)), the CDF is commonly denoted (z). (z) is a continuous, monotone increasing sigmoid function whose domain is the real line and range is (0,1). As an example, consider the familiar fact that…mehr

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High Quality Content by WIKIPEDIA articles! In probability theory and statistics, the probit function is the inverse cumulative distribution function (CDF), or quantile function associated with the standard normal distribution. It has applications in exploratory statistical graphics and specialized regression modeling of binary response variables. For the standard normal distribution (often denoted N(0,1)), the CDF is commonly denoted (z). (z) is a continuous, monotone increasing sigmoid function whose domain is the real line and range is (0,1). As an example, consider the familiar fact that the N(0,1) distribution places 95% of probability between -1.96 and 1.96, and is symmetric around zero. It follows that