Exploring Research Methodology: A Comparative Analysis of Qualitative and Quantitative Data Analysis Techniques

Introduction

Research is the systematic investigation into the study where the materials and the sources of the information and data are evaluated and analyse well to establish the facts and figure and reach the new conclusion (Kraus, Ribeiro-Soriano and Schüssler, 2018). The researchers try to conduct innovative research systematically to increase the stock of knowledge and explore new application of the theories and models successfully. In this research context, the researchers try to gather data and information and analyse the collected at and information by applying effective data analysis technique. If you are seeking data analysis dissertation help, our services are there to provide the support you require in place to navigate through this challenging process. There are two types of data analysis technique, which are qualitative and quantitative analysis and both the data analysis technique are effective for the researchers to develop proper understanding about the research topic after analysis the data and information critically. Both the data analysis techniques are important for the researcher to draw proper conclusion after conducting the research and analysis and successful evaluation. Hereby, data analyses and evaluation depends on the correct data analysis technique which provides a scope to improve understanding and conduct appropriate analysis of the data and findings for further conclusion (Johnston, 2017). The qualitative and quantitative data analysis techniques are different to each other and it is important to dignify the advantages and disadvantages of each of the data analysis technique.

Qualitative data analysis

Qualitative data analysis technique is the range of process and procedure where the researchers move from the qualitative data that have been collected in to a form of explanation, analysis and evaluation so that the researchers and the readers can understand the research topic and develop effective knowledge from proper explanations. The qualitative data analysis is usually based on the interpretative philosophy, where the data and information are interpreted well with appropriate explanation by analysing the collected theories and models from some secondary sources of information (Bengtsson, 2016). In this regard, the researchers collect secondary sources of information for conducting the qualitative data analysis, where the gathered data and findings would be analysed on the bass of the existing theories, concepts and knowledge related to the research topic. The qualitative data analysis is advantageous for the researcher as it allows focusing on hidden aspects of the organisations as well as it clarifies the roles of the researcher in producing the organisational accounts. Organisational process and events can be understood by the qualitative data analysis technique. However, there are some disadvantages such as it is not easily acceptable and it needs long period of time, where the researcher may face problems and difficulties in gather the valid data for conducting the qualitative data analysis (Gaber and Gaber, 2018).

Quantitative data analysis

On the other hand, there are different techniques of conducting the quantitative data analysis technique, where the researchers try to develop suitable analytical tools and technique to analyse the gathered data such as SPSS tools. It is defined as the value of data in the firm of counts and numbers, where each data set has numeric numbers and the researcher utilises statistical survey, polls and questionnaire to collect the valid data. For conducting the quantitative data analysis, the researchers require to have primary data, which can be gathered through survey, online questionnaire and interview where the numeric data are gathered well. With proper statically analysis, the researchers try to identify the relationship between the dependent and the independent variables in the research topic (Bryman, 2017). Additionally, the quantitative data analysis is effective, where the researchers can provide statistical interpretation by utilising the numeric data and information which would be effective for successful analysis and exploring new values and understanding. There are four types of quantitative data analysis, which are descriptive statistics, correlation, quasi experimental and experimental, and all the techniques are beneficial for the researchers to draw conclusion after appropriate analysis of the gathered data statically (Colorafi and Evans, 2016). The advantages of utilising quantitative data analysis are larger sample size, supports generalisation, researcher interference can be avoided and the research can be replicated. On the other hand, the major disadvantages of the quantitative data analysis are difficulties in collecting valid and reliable data and reaching the people who can provide authentic information, problems in question design, critical situation in conducting survey and gathered data can be narrow and superficial (Hammersley, 2018).

Differences in the qualitative data analysis and the quantitative data analysis

The above mentioned two data analysis techniques, qualitative and quantitative are different and the technique have different ways to analyse the data and information and the research. The differences of the qualitative data analysis and quantitative data analysis will be described further.

Conclusion

Hereby, the qualitative data analysis and quantitative data analysis technique is different to each other, where explanation is developed under the qualitative technique and statistical interpretation is developed under quantitative data analysis technique.

Reference List

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