Data Methodology : How Ab 109 Affect Recidivism Within Butte County

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Data Methodology
Our data consists of 72 individuals who were affected by the implementation of AB 109 in California. We focused on how AB 109 was to affect recidivism within Butte County, and decided to focus our research on age, ethnicity, and the number of previous convictions. For our data, we used a dataset that was provided, which focuses on the California Realignment from AB 109, and lists different facts about each person in Butte County who were affected by the change. This data provided information specifically on our hypotheses questions, in which we could compare to the listed recidivism rates. For the provided dataset, we looked at the available variables in order to find what would work best for our research question. We decided that the “rearrested after release to PCRS” variable would work best to represent recidivism. This indicated whether or not someone was rearrested for a crime while they were still under supervision within the program. We easily found variables for the people within the dataset regarding their ages and ethnicity because it was included in the raw data. Someone else had previously recoded the variable for age into categorical age groups to make the data easier to work with and interpret.
In order to have a variable for the people’s criminal history, we decided that looking at the variable “Previous adult convictions” they have on their record would be the closest fit we would have. In order to make this variable work for our…

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