In this post, I will discuss how proper choice and effective management of statistical software contributed to significant improvement in data analysis and overall time management of my PhD study. The doctoral study may seem a long journey to many unless they get into their analysis part of dissertations. Then people may find themselves with minimal time. Therefore, the effective use of time is a must thing for all higher-degree-by-research students. The choice and management of proper statistical analysis tool can help students to optimise their time.
I started my analysis of data after successful completion of confirmation of candidature, accomplished in January this year. My method of analysis is quantitative in nature; hence, the investigation involves the use of statistical software to present my research findings. I had experience in using several analytical tools before I started my doctoral study at Western Sydney University. But I never had an experience of working with “Big Data” which was the case for my PhD study. I felt that the software I used was not performing at its best. I changed my way to use it so that the desired result could be achieved in minimum possible time. This was a new learning-by-doing experience for me because I did not find any significant difference in time previously to obtain results with the way I used that software. But I was not still satisfied. An example may clarify the problem. I had to wait more than one hour to get the mean of a variable, a basic statistic in any quantitative analysis. Obviously, my analysis is more than finding basic statistics, and I cannot imagine how much time it would take for complex computation. I do not blame “STATA.” entirely for my difficulties because my computer workspace was constrained with limited memory. Increasing memory was not a possibility because it would incur a lot of costs resulting in surpassing my allocation of research fund. As a result, I was looking for an alternative.
Fortunately, I found a workshop on advanced R programming in the month of February this year, organised by the Graduate School of Western Sydney University. I took the opportunity to register myself for the workshop in no time. In the workshop, I found two important things- how the use of R can speed up my process of analysis and how to use it most efficiently. These were challenges I was facing with my previous software named “STATA”.
Overall, I found the training quite helpful. It was an opportunity to learn industry-demanding software, which not only solved my ongoing research problems but also enhanced my skill in quantitative analysis. The mentor welcomed us to have electronic communication to improve our understanding if required. He also encouraged us to go through more advanced topics by ourselves so that we can utilise the useful features of this tool in our research. In this way, I learned more aspects of this fantastic subject matters and used it effectively to overcome the challenges of the data analysis part of my thesis.