Content

Content

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Sheet 1_var

The approach adopted in the course

a probabilistic perspective
a process perspective

Data types and observations

From observations to variables: the role of uncertainty

Uncertainty and risk: risk set and exposure

Sheet 2_var

Introduction to probability theory and statistical inference

Observations and random experiments
Random variables and probability distributions

Continuous random variables
Discrete random variables

Sheet 3_mle

Plausible observations and plausible models: the maximum likelihood method

Sheet 4_loglin and 4_loglin3

Analysis of count data: introduction to log-linear models

The Poisson probability model
The log-linear model

Sheet 5_lograte

The log-rate model: statistical analysis of occurrence-exposure rates

Construct your own logistic regression model

Logit model, logistic regression, and log-linear model: a comparison

Models of counts: log-linear model
Logit model and logistic regression

Data on political attitudes (Payne)
Data on leaving home

Construct your own logistic regression

Incomplete data: indirect estimation of migration flows.

Sheet 8_summary

Summary

Sheet 9_bookweb

References: books and web sites