Unit VII Final Project 14 Of Course Grade Final Submission

Unit Vii Final Project14 Of Course Gradefinal Submission

This assignment encompasses the development of a comprehensive community health program presentation and a discussion on data science problem-solving approaches. The first part requires creating a narrated PowerPoint presentation that integrates various components from your course work, demonstrating the process of identifying and addressing a public health issue in a community setting. The second part involves analyzing a data science problem, evaluating models for abstracting data complexities, and discussing their differences using a comparative table.

Paper For Above instruction

Public Health Program Development and Evaluation

The culminating project in this course involves synthesizing your understanding of community health issues, social determinants, assessment processes, program planning, and sustainability strategies into an effective presentation. The goal is to communicate a proposed health intervention clearly to community stakeholders through a narrated PowerPoint presentation.

The presentation begins with a title slide displaying the presentation title, your name, Columbia Southern University, and the date. It continues with an introduction of the public health issue in the community, underpinned by relevant data and evidence from Unit I that justifies the problem's significance. Contextualizing the issue using statistical data emphasizes its impact and frames the need for intervention.

Next, the presentation discusses social determinants outlined in Unit II that influence or contribute to the health issue. This section explores socioeconomic, environmental, behavioral, and cultural factors that shape health outcomes and must be addressed for the success of any intervention.

The community health assessment component, based on findings from Unit III, identifies the specific needs and assets of the community. This involves a review of data collected through surveys, interviews, or existing health records, highlighting priority issues that require targeted interventions.

The plan proceeds with a detailed discussion of the program evaluation strategy chosen in Unit V. Here, you explain the evaluation model (e.g., formative, summative, process, or outcome evaluation), including specific components such as indicators, data collection methods, and timelines. Articulating how evaluation will measure success or areas for improvement ensures accountability and continuous quality improvement.

Finally, the presentation addresses sustainability strategies discussed in Unit VI, demonstrating how the program will be maintained long-term. This includes securing funding, fostering community partnerships, integrating the program into existing health systems, or policy development to ensure ongoing impact beyond initial implementation.

The presentation must include at least 10 slides, excluding the title and references slides. Audio narration is required for each slide, with the transcript included in the notes section. Proper citations should be integrated where applicable to support content and data presented.

Analysis of Data Science Problem Solving

In addition to the community health project, you are tasked with discussing a real-world problem best solved by data science. Your discussion should include a logical explanation of why data science offers an effective solution, emphasizing the power of data-driven decision-making. Respond to peers by suggesting alternative approaches, considering different models or methods that could address similar problems.

The second component involves a comparative evaluation of different models used to manage complexity in data science. Using a table, summarize the key differences and similarities among these models, covering aspects such as purpose, methodology, advantages, and limitations. This comparison helps clarify why certain models are appropriate depending on specific data scenarios.

This segment requires a minimum of 300 words, double-spaced, formatted according to APA standards. Use screenshots if applicable to illustrate model differences or data management techniques. References include foundational texts by Samuel Burns and Deborah Henderson, highlighting concepts from basic data science principles to data management strategies.

Conclusion

This combined assignment emphasizes deploying comprehensive planning and analytic skills—from designing community health initiatives to understanding complex data models. Effectively communicating these processes through presentation and analysis fosters professional growth and contributes to public health improvements and data science proficiency.

References

• Burns, S. (n.d.). Chapter 1: Basic concepts of Data Science. Amazon KDP Publishing.
• Henderson, D. (2017). DAMA-DMBOK: Data Management Body of Knowledge (2nd ed.). Technics Publications.