Characteristic |
Beta |
95% CI 1 |
|---|---|---|
| type | ||
| Bicycle theft | — | — |
| Burglary | 231 | 7.2, 519 |
| typeCriminaldamageandarson | 230 | 7.6, 519 |
| Drugs | 232 | 9.5, 520 |
| typeOthercrime | 231 | 9.0, 519 |
| typeOthertheft | 229 | 6.1, 517 |
| typePossessionofweapons | 232 | 9.9, 521 |
| typePublicorder | 231 | 8.7, 519 |
| Robbery | 70 | -711, 464 |
| Shoplifting | 232 | 9.6, 520 |
| typeTheftfromtheperson | 230 | 7.0, 519 |
| typeVehiclecrime | 229 | 7.2, 518 |
| typeViolenceandsexualoffences | 231 | 8.4, 519 |
| 1
CI = Credible Interval |
||
Model
\[
\text{SuspectIdentified}_i = \beta_0 + \beta_1 \cdot \text{type}_{i1} + \beta_2 \cdot \text{type}_{i2} + \cdots
\] For this formula: - ( _i ) is the binary outcome for the (i)th observation, indicating whether a suspect was identified (1) or not (0). ( _0 ) is the intercept term. ( 1, 2, ) are coefficients for each category of the type variable, which represents different types of crimes. ({i1}, {i2}, ) are dummy variables corresponding to each crime category, excluding the reference category.