Human beings are inquisitive creatures. Since the beginning of time, they have measured, categorized and attempted to understand the world around them. On a daily basis, you can hear these efforts on the evening news and read them in your favorite magazine. Furthermore, to meet this goal, scientist and intellectual explorers arm themselves with the science of statistics. Statistics are applied all in the name of learning something new, proving a point, or perhaps reluctantly admitting there is no connection between two phenomena. The concept of descriptive statistics, the application of descriptive statistics to my own study using a small data set, as well as an example of correlation will be examined.
Descriptive Statistics
For me, the best thing to do when overwhelmed by something is to organize it. In addition to the organization of data, it is desirable to share information about the data in a transparent and concise manner. According to Blessing and Forister (2013), when utilizing descriptive statistics to organize your data the “key concepts are measures of central tendency and measures of variability” (p. 194). These concepts are accomplished by using mean, median, mode, as well as, standard deviation, range and standard error. There value lies in the ability to give information about a set of data, without giving all of the data. There are various situations suited to the different elements of descriptive statistics and it is important to keep in mind the type of data you are using (ordinal, interval, ratio) when selecting the descriptive statistics for your study. In my research study regarding telehealth and 30 day readmission rates, descriptive statistics would be interesting to observe central tendencies for age of th...
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In conclusion, statistics offer a way to organize, measure and understand large sums of data. The way this organization happens depends on the type and size of the data, as well as, the questions trying to be answered. Descriptive statistic’s key concepts are measures of central tendency and measures of variability. In addition, correlation is helpful to find relationships between variables, but not the cause of the relationships. Lastly, it is important to represent your data in an honest and straightforward manner to maintain trust and credibility in the scientific community.
Works Cited
Blessing, J., & Forister, J. (2013). Introduction to research and medical literature for health professionals (Third.). Burlington, MA: Jones & Bartlett Learning.
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The final chapter of this book encourages people to be critical when taking in statistics. Someone taking a critical approach to statistics tries assessing statistics by asking questions and researching the origins of a statistic when that information is not provided. The book ends by encouraging readers to know the limitations of statistics and understand how statistics are
Page-Reeves, J., Niforatos, J., Mishra, S., Regino, L., Gingrich, A., & Bulten, J. (2011). Health
10). Other characteristics include a focus on the objective and quantifiable, emphasis on specific concepts, the researcher is an external, large sample, measured information, and includes statistical analysis (Polit & Beck, 2017). The use of quantitative methodology fits this study’s purpose because it asks specific questions about how frequently the phenomenon occurs, what factors are related to the stated phenomenon, and what is the underlying cause (Polit & Beck, 2017). It also asks what would happen if the phenomenon was altered, and can the occurrence be prevented (Polit & Beck,
The outcomes of the analysis, though, require to be understood with concern, predominantly when looking for a fundamental association or when using the regression equation for prediction.
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The purpose is to explain, predict and or control phenomena through a focused collection of numerical data. Answers the question what, when and where. Sampling is a large population that is random. The design is structured, inflexible, specified in detail (Quantitative, Qualitative Research, 2012). Data collection focus groups and interviews. Data interruptions are conclusions and generalizations at the end of the study, never one hundred percent sure of the outcome. Used to study individual cases and find out how people think or feel (Broader, 2010). Quantitative studies provide more in-depth information that is specific to an issue can often be used for comparison. Quantitative data offer inferential statics, a collection of data about millions of people and make inferences about a target population. The data include gender, height weight, cholesterol level, waist circumference and temperature, ages, geographical region or population and can be anonymous. It helps to measure trends over time such as frequency of outbreaks of communicable diseases in a community. Quantitative enables the ability to summarize allows for comparisons over time and across categories information sources. Quantitative has higher accuracy, eliminates bias, proves or disproves a hypothesis and narrows directions if further research is needed. Quantitative can assist nurses in determine which scientific method to determine which
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When caring for patients it is fundamentally important to have a good selection of up to date evidence Based Practice clinical articles to support research strategies, this allows professionals to assemble the most resent and accurate information known which enables them to make decisions tailored to the individual’s plan of care. It is essential to have clinical expertise and have the involvement from the individual patient, they must have full engagement and incorporation in order to have the accurate evaluation.
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In the health care industry, gathering information in order to find the best diagnosis route or even determine patient satisfaction is necessary. This is complete by conducting a survey and collecting data. When the information is complete, we then have statistical information used to make administrative decision within the healthcare field. The collection of meaningful statistics is an important function of any hospital or clinic.
Ed. David Zieve. U.S. National Library of Medicine, 26 Feb. 2014. Web. The Web.
Whether or not people notice the importance of statistics, people is using them in their everyday life. Statistics have been more and more important for different cohorts of people from a farmer to an academician and a politician. For example, Cambodian famers produce an average of three tons or rice per hectare, about eighty per cent of Cambodian population is a farmer, at least two million people support party A, and so on. According to the University of Melbourne, statistics are about to make conclusive estimates about the present or to predict the future (The University of Melbourne, 2009). Because of their significance, statistics are used for different purposes. Statistics are not always trustable, yet they depend on their reliable factors such as sample, data collection methods and sources of data. This essay will discuss how people can use statistics to present facts or to delude others. Then, it will discuss some of the criteria for a reliable statistic interpretation.