As it has already been mentioned in the preceding papers, the problem of falls in hospitals is significant and requires immediate action. The project tests the efficiency of the proposed methods of fall prevention on two groups, one of which will undergo interventions and another one will not. The project aims at achieving a statistically significant difference between these two groups. The data on the research participants will be collected and analyzed via the Statistical Package for Social Sciences (SPSS) Software that allows to reveal trends in the collected data, find the standard deviation, and determine the most efficient sample size.
The SPSS was chosen because it allows to compare and conduct correlational tests between multiple variables (Ong & Puteh, 2017). In the given project, the variable is the frequency of falls in both experimental groups. The changing variable, therefore, is the methods applied to diminish the number of falls. Apart from analyzing the gathered data, the SPSS allows the researcher to test the null hypothesis (Larson-Hall, 2015). For the current research paper, the hypothesis that the proposed methods of fall prevention are effective will be tested at the 0.05 significance level. This means that the author believes that the author estimates that the suggested hypothesis is true with 95 percent of probability and that there is a 5 percent of risk that the hypothesis is false.
To conclude, in the research on fall prevention, the author uses SPSS Software to analyze data and test the hypothesis. SPSS was chosen because it is a user-friendly tool that allows to test relations between multiple variables and, thus, ensure the final results’ credibility (IBM, n.d.). The null hypothesis test will be based on the analysis of data retrieved from testing two groups of patients, one of which will experience interventions aimed at fall prevention.
References
IMB (n.d.). IBM SPSS Statistics. Web.
Larson-Hall, J. (2015). A guide to doing statistics in second language research using SPSS and R. Routledge.
Ong, M. H. A., & Puteh, F. (2017). Quantitative data analysis: Choosing between SPSS, PLS, and AMOS in social science research. International Interdisciplinary Journal of Scientific Research, 3(1), 14-25.