Evaluate potential program models using peer-reviewed journals.
Explain how data impacts these models. For example, explain how the impact model addresses hunger among the homeless.
- Introduction: In a paragraph, introduce your organization, describe their mission, and define whom they service.
- Background: Analyze the background of a chosen organization including population served, governance structure, how it has evolved over time, et cetera.
In the background section of the final paper, you will provide a detailed profile of your chosen organization including the population served, governance structure, and internal and external stakeholders.
Include how the organization’s role has changed over time.
This section should be two full pages.
- Identify relevant researched data sets to discover a community problem.
- Turn in a table of data that lists the categories and their matching data for your chosen problem in your organization. For example, 28 men, 42 females, six unidentified (Refer to Riverbend City: Interpreting Data).
Report on the history of risk assessment and decision making.
- For example, victims of domestic violence and sexual abuse.
If you are familiar with statistics, feel free to include information regarding decision making, such as sensitivity, specificity, and positive predictive value.
For example, the probability is that cancer is present when the test is positive.
- Specificity: Whatever you are testing needs to test negative, which means that there will not be enough services for the population.
- For example, the test result is negative because cancer is not present.
Sensitivity: Whatever you are testing needs to test positive, which means that there will be enough services for the population.
- For example, what is the probability that there would not be enough services for the homeless?
- For example, sensitivity is when the test will be positive when cancer is present.
Positive Predictive Value means the probability that something, such as a disease, is present when the test is positive.