Introduction
Data analysis is a method of dealing with data obtained from a field study or research carried through other means of experiments. Analysis aims at ensuring that information is extracted from the data collected hence helping the researchers to study it and derive conclusions regarding their subject of study.
Depending on the subject being evaluated by the research, analysis methods may differ due to the diverse nature of subjects put into consideration (Good, 2001).
The main factor that is considered when analyzing data is the mode of collection. This is because, data available for analysis differ depending on the method used in the collection. For example, data collected by observation should be analyzed using methods different from that used to analyze data collected through measurements.
Body
First of all, data from the field is assembled in order to make analysis easy. For example, all collected data can be fed into a computer in formats which software can be able to interpret. Statistical data tests are used in comparison of data, and test to be used depends on the sample size.
There are two tests commonly used in statistical data namely, parametric and nonparametric. Non parametric tests do not make assumptions about samples; therefore, statistical test to be used depends on samples of data put into considerations (Good, 2001).
After data is analyzed, the findings are displayed in various ways aimed at ensuring data is presented to its audience in the simplest way possible. This means that the findings may be displayed in graphs or pie charts representing the whole population considered for study.
The representation of data should be done in a way such that the purpose of the research will be evident from the data displayed on the graphs and charts. When reporting, the findings must be expressed in a way such that to show the significance of the research. The scope of the survey should be made clear in order for the audience to understand the essence of the report.
The report should explain clearly whether the research answered research questions. If it failed to answer the questions, then the audience should think for other means of getting answers to the unanswered research questions (Kanji, 2006). This means that the research may be repeated with the aim of answering the questions which are necessary for the researchers.
In addition, they should be able to tell whether the set hypothesis was true or false. The report should be written and presented in a manner such that the research design used to arrive at the conclusion. This is because the researchers need to be careful when choosing research designs, in order to analyze their raw data and be able to come up with useful conclusions.
Data may be collected by either observations or by use of questionnaires which respondents may be required to fill (Kanji, 2006). This helps the researchers to reach all respondents regardless of how busy they might be, because they will be required to fill the questionnaires at their own free time and deliver it to the researchers.
Conclusion
In fact, data analysis should be taken seriously to avoid contradicting the essence of the whole research conducted. This means that data analysis and reporting should be done in a way such that the significance of the survey. It should lead to writing of an inclusive report detailing all aspects encountered during the research. It should give the details regarding recommendations made by the researchers to their audience.
References
Good, P. I. (2001). Resampling methods: a practical guide to data analysis. London: Birkhäuser.
Kanji, G. K. (2006). 100 statistical tests. New York: SAGE.