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Nov 06, 2021
    • Week 1, you analyzed a pre-intervention elementary school asthma database from the perspective of a public health informatician. This week, you will review the data set in more detail and discuss the tools informaticians use. For the asthma data summary, you will use your Excel Spreadsheet and Pivot Table reports. You will then answer the following questions in the form of a 34-page summary statement that includes the data as well as an interpretation of the findings. The Pivot Tables need to be embedded in your report to explain the summary results.
      What summary results do your pivot tables demonstrate about this grade school population of students? Use the following questions to prepare your paper.

      Data Frequency Questions:


      Begin with an explanation of the tools of informatics, including spreadsheets, relational database technologies, and integrated statistical packages. Why are these tools and technologies so important when managing large databases of public health informatics?
      Database Analyses

      • Are there more males or females in the survey population?
      • Which condition has the highest frequency?
      • Which month had the highest number of students with breathing difficulties?
      • Which school had the highest frequency of students with bronchitis?
      • Which gender has the highest frequency of asthma?
      • How many students answered yes to Reactive Airway Disease (RAD)?
      • What is the percentage of students with RAD that have been prescribed medication?
      • Which zip code has the highest number of students living in it?
      • Of that zip code, which condition had the highest frequency?
      • How many students answered yes to all four conditions: asthma, RAD, bronchitis, and wheezing?
      • Based on all four conditions and zip code, are the conditions evenly distributed among the survey population?
      • Does one school have more students in the affected zip codes and with all four conditions than the others do?
      • Summary:
      • Explain your data analyses results and describe what data quality assurances you applied to ensure your results are accurate.
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