The main purpose of this survey is to determine the demography of nurses in the region and to determine their level of education as well as the intention of advancing in their career. Understanding the purpose of the study is very essential in data analysis. This serves as the first rule in data analysis. In this research the independent variable included age, gender, level of education and other aspects that can be used to classify nurses. The dependent variables in this case were nurses. The research targeted all nurses though they are further classified based on other independent variable. Identification of independent variables is very important in data analysis and it serves as the second rule in data analysis. Based on this result, it is surprising that the highest population of nurses in the region is between 45 and 49. This may imply that young people are no-longer interested in this field. It may also imply that the number of nurses intending to purse advanced education is low since most individual in the old age do not intent to waste their time studying (Houser, 2015).
The next data analysis rule is the identification of how variable are evaluated. The survey permitted for data containing different measurement levels. The current survey allows for counting of the research results and no measuring them due to the discrete nature if the evaluated aspects. Therefore the survey data can be analyzed using different statistical evaluation techniques including comparison. The fourth data analysis rule involves measuring of the central tendency and the evaluation of variability for variable studies. This involves the evaluation of the data categories and the meaning of the data based on the survey. This can easily be measured in an extensive survey where respondents are involved and not a narrow survey as demonstrated in this case (Houser, 2015).
Houser, J. (2015). Nursing research: Reading, using, and creating evidence (3rd ed.). Sudbury, MA: Jones & Bartlett
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