Infection Bayesian Model

Model Defintion

\[\Large y_i = \epsilon_i + \beta_1 x_{1,i}\] with \(y = Infected~Count\), \(\epsilon_i = Unkown~Values)\), and \(x_1 = Sex\).


Characteristic exp(Beta) 95% CI1
    Female 2.34 2.12, 2.56
    Male 2.08 1.87, 2.30
1 CI = Credible Interval

On the-left hand side of the Model Definition the outcome is defined as the Infected Count, the variable to be explained.

The right hand side of the model incorporates two parts, what we know and what we don’t know.

\[\Large \epsilon_i + \beta_1 x_{1,i}\]

\(\Large \epsilon_i~\) describes the inexplicable factors in our outcome, including any affects that have an influence on a person’s ability to contract E.Coli, but are not related to the person’s sex.

\(\Large \beta_1 x_{1,i}~\) consists of the parameter, Sex, and the respective data points.