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Health Program Data Analysis

What does it mean to analyze the collected data from a program evaluation? An analysis involves reviewing multiple components, such as analyzing and synthesizing findings. This includes tabulating information to explore how many individuals participate in the program, reviewing demographics, analyzing the number of participants achieving the outcome goals, and analyzing and stratifying data by race, gender, age, income level, and geographic locations. It is also important to conduct a comparative analysis to review strengths, weaknesses, and any limitations and to review gaps. The next step is combining all of this information to make decisions and present to stakeholders for further input and suggestions regarding the program.

Using the Internet, obtain scholarly articles and materials to draw inferences and support your philosophy.

Respond to the following:

Compare and contrast qualitative and quantitative methods used for designing a program. (Use a 2x2-table format to present your analysis).

Review the decision tree for statistics. You can review the tree online at the following:

The Decision Tree for Statistics. (n.d.). http://www.microsiris.com/Statistical%20Decision%20Tree/

After reviewing the information:

  • Select three public health statistical methods that you would use in a public health program for your selected health issue or health disease topic.
  • Provide a complete analysis for each statistical method.
  • Explain why these methods are important and what data or information you could obtain for your program.

Write a 1-paragraph response. Support your methods with appropriate examples and scholarly references. Comment on the postings of at least two peers with scholarly information.

Evaluation Criteria:

  • Compared and contrasted qualitative and quantitative methods used for designing a program.
  • Recommended three feasible public health statistical methods that you would use in a public health program for your selected health issue or health disease topic.
  • Analyzed each statistical method in detail.
  • Explained why your selected statistical methods are important and what data or information you could obtain for your program.
  • Responses demonstrated an in-depth research and analysis.
  • Justified your answers with appropriate research and reasoning.

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