Inferential Statistics

Assignments/JTownsend_Module_04_Written_Assignment_-_Organizing_and_Displaying_Data_11214.docx

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Organizing and Displaying Data

Organizing and Displaying Data

Rasmussen College

Jordan Townsend

Sunday, November 2, 14

A frequency distribution is commonly used to categorize information so that it can be interpreted quickly in a visual way. A situation where frequency distribution would be used to organize data could be to conduct a survey on how many hours of sleep college students get each night. After you get that information you then need to study the numbers the student provided, this serves as the categories. Then the occurrences of each number are then tallied. This is one way how frequency distribution aids healthcare researchers/practitioners. Using the information from a frequency distribution, researchers can then calculate the mean, median, mode, range and standard deviation. Frequency distributions are often displayed in a table format, but they can also be presented graphically using a histogram.

The importance of organizing and describing data is vital to an organization. Data consist of raw facts, such as customer names, illnesses, cures, treatments, addresses, and many more. Information is a collection of facts organized in such a way that it has more value beyond the facts themselves. For example, a database of customer names and purchases might provide information on a company's market demographics, sales trends, and customer loyalty/turnover. Health care providers strive to produce effective goods and services efficiently. Statistics are important to health care companies in organizing and measuring data. By establishing benchmarks, or standards of service excellence, quality improvement managers can measure future outcomes. Analysts map the overall growth and viability of a health care company using statistical data gathered over time. Hospitals and other large provider service organizations implement data-driven, continuous quality improvement programs to maximize efficiency. Government health and human service agencies gauge the overall health and well being of populations with statistical information. Describing data is part of descriptive statistics. There are two main ways of describing data. One is mathematically, the other visually. It is surprising just how much understanding you can get from data by the use of what is really quite straightforward methods. In mathematical descriptions we'd typically use measures of central tendency, such as the mean, median and mode and measures of dispersion such as range and standard deviation. We also need to know which of these measures are the most appropriate in each situation. Additionally, Data organization is critical to optimal data use. Consequently, it is important to organize data in such a manner as to reflect business operations and practices. As such, careful consideration should be given to content, access, logical structure, and physical organization. Content refers to what data are going to be collected. Access refers to the users that data are provided to when appropriate. Logical structure refers to how the data will be arranged. Physical structure refers to where the data will be located.

In conclusion, Good data can be analyzed and summarized to provide useful information. Bad data can be analyzed and summarized to provide incorrect/harmful/non-informative information. This is organizing and describing data is very important.

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