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The homeless issue in Barstow poses a logistic regression as an extremely effective tool to have. This method predicts that the most likely outcome would be , such as whether an individual can become homeless or not, based on certain variables. For instance regression can be used to test the Barsotw homeless population through gender, educational access, and mental health service availability, which have a heavy influence on experiencing homelessness.

Collection of data in regard to administrative records, use coding of the homeless in Barstow using a dependent variable, 0-not homeless and 1-homeless. The independent variables include demographics such as age, gender, education, and thoughts about government services. In analyzing the odd ratios, policymakers can then identify variables having the most influence, such as intervention in workforce training, domestic violence shelters, or the increase of mental health funds. Overall, regression can provide a data-drivenguide to resource allocation and policies to help with the homeless crisis in Barstow.