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[Adftertesold]

It’s a natural part of living in the information age: You start to feel sick, so you Google your symptoms. Both the common cold and the flu will make you feel miserable, and because both are respiratory infections with similar symptoms - coughing, aching, headache, you know the drill - it can be difficult to know which one has you in its grip. Every year, anywhere from five to 20 percent of the U.S. While many sufferers will find relief in over-the-counter medicines, influenza can be serious. Influenza-related complications may require hospitalization, and sometimes complications can be fatal. Influenza, together with pneumonia (both are lower respiratory infections), ranked as the eighth leading cause of death in the U.S. For its tracking purposes, the CDC considers a fever of at least 100 degrees Fahrenheit (37.8 degrees Celsius) with a cough and/or a sore throat to be an ILI. Beginning on the 40th week of the year - which is the beginning of the October to May flu season - the CDC distributes weekly influenza activity reports. Likewise, quantitative data methods can be used for outlier detection that would be subsequently excluded in analysis. Data that is processed, organized and cleaned would be ready for the analysis. Various data analysis techniques are available to understand, interpret, and derive conclusions based on the requirements. Data Visualization may also be used to examine the data in graphical format, to obtain additional insight regarding the messages within the data. Statistical Data Models such as Correlation, Regression Analysis can be used to identify the relations among the data variables. These models that are descriptive of the data are helpful in simplifying analysis and communicate results. The process might require additional Data Cleaning or additional Data Collection, and hence these activities are iterative in nature. The results of the data analysis are to be reported in a format as required by the users to support their decisions and further action. The feedback from the users might result in additional analysis. The data analysts can choose data visualization techniques, such as tables and charts, which help in communicating the message clearly and efficiently to the users. The analysis tools provide facility to highlight the required information with color codes and formatting in tables and charts. nevada caucus

















































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[wangiskahn2]

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