Analyzing Discrete Survey Answers
Ulrich Schneider
Comments
This course focuses on estimating models with discrete dependent variables, presenting a rigorous academic exploration of statistical methods and their application to real-world datasets. Through an examination of maximum likelihood estimation and various models, including linear regression, binary models (logit and probit), multinomial models, and count data analysis, students will gain a comprehensive understanding of the complexities inherent in analyzing discrete outcomes. Hands-on exercises using \texttt{R} software will provide practical experience in model implementation and interpretation, enabling students to conduct sophisticated data analysis with precision and confidence.
- Introduction
- Maximum Likelihood
- Linear Models
- Binary Models
- Multinomial Models
- Models for Count Data
- Generalized Models for Discrete Outcomes
12 Class schedule
Regular appointments
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