Binary logistic regression

why a yes/no outcome breaks linear regression; odds, odds ratios and the log odds, explained with arithmetic rather than assertion; coding the outcome so the odds ratio points the right way; the menu path including Categorical and Options; reading the output - omnibus test, Nagelkerke R-squared, Hosmer-Lemeshow, the classification table, and the variables in the equation; interpreting Exp(B) and its confidence interval in a sentence; adjusted vs unadjusted odds ratios; events-per-variable and how many predictors your sample can carry; APA reporting and the OR table.