Statistical Analysis

Statistical Analysis
Introduction
When conducting any research form, it is always imperative for the researchers to collect data and analyze them using the best research analysis tools. Several tools can be used in analyzing research data, and the most used methods are statistical analysis. Statistical analysis is the process through which research data are collected and interpreted so that the patterns of variables used in the research can be uncovered. The research that was conducted by Marso et al. (2016) on liraglitude and cardiovascular outcomes in type 2 diabetes used different statistical methods in their analysis, and this is what the research will analyze.

Statistical Methods

Through the research, different methods were used by the researchers to analyze the data that they collected during the research process. The first statistical method that the researchers employed is graphing. The graphs were mostly used to show the time-to-event analysis, which consisted of the first occurrence of death from cardiovascular causes. From the study presented in the research, it is clear that the researchers used the statistical method of graphs appropriately as it gives a clear indication of the first occurrence of death from different causes at different hazard levels. These graphs are ultimately providing an analysis of what the researchers wanted to get from their research. Therefore, the use of graphs in analyzing the research data was utterly appropriate.

The next statistical method used in the analysis of research data is descriptive statistics in which the P-Value of the research data was analyzed. The P-Value is mostly used in research data analysis to show the significance of the data collected. The data can only be significant if the P-Value is 0.05 or less. Some of the data were significant from the calculated P-Value, while others are not significant to research based on the P-Value. P-Value’s usage as a method of descriptive made it possible for the researchers to identify the insignificant data. The use of P-Value as a statistical method of data analysis was done appropriately and

thoroughly.

The readability of the article is authentic. The article is presented chronologically with the correct choice of words. The sentences used are not long or either short. They are meticulously organized, for the readers can quickly grasp what the report is all about. Apart from the research report being readable, the data’s validity was valid as collected by the researchers. The kind of information that the researchers wanted to get from the research was achieved. The study’s validity was carried out through diachronic reliability, where data collected were observed over time, which were used in the analysis of the research. Therefore, the readability and validity of the report were appropriate and complete as they are used.

On the other hand, the report did not use different statistical methods, including sampling and center and spread measures. But the methods that were used by the researchers made the report as articulated complete.

 

Reference

Marso, S. P., Daniels, G. H., Brown-Frandsen, K., Kristensen, P., Mann, J. F., Nauck, M. A., … & Steinberg, W. M. (2016). Liraglutide and cardiovascular outcomes in type 2 diabetes. opens in the new window New England Journal of Medicine, 375(4), 311-322.

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