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This lecture covers the application of logistic regression in analyzing horseshoe crab data. Topics include the sexual biology of horseshoe crabs, logistic regression model interpretation, odds ratio, model fitting, and parameter estimation. The instructor discusses the importance of the exponential family in generalized linear models and the use of the logit transformation. Practical examples and computer output for logistic regression models are presented, along with the estimation of probabilities and odds ratios. The lecture emphasizes the significance of binary response variables and the methodology for maximum likelihood estimation.