Logistic regression: Difference between revisions

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where <math>\beta_0 = -\mu/s</math> and is known as the [[vertical intercept|intercept]] (it is the ''vertical'' intercept or ''y''-intercept of the line <math>y = \beta_0+\beta_1 x</math>), and <math>\beta_1= 1/s</math> (inverse scale parameter or [[rate parameter]]): these are the ''y''-intercept and slope of the log-odds as a function of ''x''. Conversely, <math>\mu=-\beta_0/\beta_1</math> and <math>s=1/\beta_1</math>.
 
Remark:Note Thisthat this model is actually an oversimplification, since it assumes everybody will pass if they learn long enough (limit = 1). The limit value should be a variable parameter too, if you want to make it more realistic.
 
===Fit===