Want to turn your collected data into something that shines bright in journals and the academic world? Then knowing the tools for data analysis is a must thing to do. Research has shown that more than 55% of the collected data goes unused and is not included in the analysis process. It is a large chunk of information that you are missing out on. So, what can you do to make sure that your data does not go unused? The answer is simple and lies in conducting a good data analysis in dissertation writing.
Now, the problem is that many of you also do not know the means of analysing huge amounts of data, i.e., tools. So, keeping all these things in mind, today’s article is about discussing the top 7 tools that can help you conduct a good data analysis. However, before moving forward, let’s explain the data analysis and its importance in a dissertation.
What does it mean by data analysis? Explain with importance.
Data analysis is a process of cleaning, analysing, and visualising data in order to achieve some goals. Those goals can be getting newer insights, driving smart decisions, or making effective public policy. In this process, you use different statistical tools to get insights into the topic. So, data analysis in dissertation help you turn the raw data into meaningful statistics, information, and explanations.
Here the question arises why is data analysis important? It has huge importance in research, i.e., dissertation, because it makes the study of collected data a lot easier and helps you unearth the hidden patterns easily. Also, the data analysis helps you establish the true relationship between the research variables. Additionally, it helps you straightforwardly interpret the collected data so that you can derive useful insights from the research problem. It is a fact that most of the students face difficulties in data analysis when working on their own, and hence they prefer to get masters dissertation help from a good firm. However, using some of the tools, they can also easily enhance their capability to work on data analysis.
7 most helpful data analysis tools in a dissertation
Data analysis tools are defined as the means of analysing large chunks of data and presenting that data in the form of charts, tables, and diagrams. Various tools and methods of data analysis in dissertation have been developed over the past decade. However, a brief description of the 7 most helpful tools is as follows:
1. SPSS (IBM)
Statistical package for the social sciences (SPSS) is probably the most widely used data analysis tool in research. Its most common use is in human behaviour research, i.e., sociology and psychology. This tool offers the ability to compile descriptive analysis easily. It also has the ability to provide you with graphical depictions of the analysis results through GUI. In its most advanced form, this tool also offers the function of creating scripts to automate the analysis and conduct more advanced analysis.
2. R (R Foundation for Statistical Computing)
R is another very useful and free statistical data analysis tool widely used in sociology, psychology, and other fields. This tool has plugins that can be added to a greater number of applications, thus making the data analysis in dissertation easier. While R is a powerful data analysis tool, it also has a steep learning curve. It includes coding your analysis, which may be a difficult task for you. However, R comes with an active community where you can discuss the problems and make your analysis more useful.
3. MATLAB (The MathWorks)
MATLAB is another analytical platform developed mainly for scientists and engineers. This tool has the ability to perform a number of analyses, e.g., regression analysis. Like R, this tool also requires the dissertation data analyser to create his own code and then analyse the data. However, plenty of toolboxes are available to help you develop the code, e.g., EEGLab. One thing is obvious: this tool is not for novice researchers. It requires a massive amount of experience and coding knowledge to perform the data analysis.
4. MS Excel
However, not a cutting-edge solution for performing effective data analysis in dissertation, MS Excel does offer a good analysis. It is probably the easiest and most widely used data analysis tool by novice researchers due to its powerful ability to create attractive graphs, charts, and diagrams. Access to this tool is very easy, and all you need to do is buy its premium subscription. All in all, it is a great option for student researchers who want to know the basics of their data and are not good at coding.
5. SAS data analysis tool
SAS is an abbreviation for Statistical Analysis Software. It offers two options for data analysis. You can either use its built-in GUI or create your own scripts, i.e., codes for the data analysis. SAS is not a free-to-access tool, and you have to buy its subscription. However, with this tool, it is highly possible to create valuable and publication-worthy graphs, charts, and diagrams. Coding the analysis can be a difficult task for you if you are a new researcher. Therefore, it is better to work with GUI.
Tableau is another very famous and widely used data analysis tool in dissertations, especially business dissertations. The motto of this tool provider is that successful business strategies are driven by the data. So, it is a very powerful data analysis and visualisation platform where you can connect all your data and create interactive dashboards. The analysis keeps updating as more and more data comes in.
Minitab is a relatively new tool in this business. However, it offers a range of both basic and advanced data analysis tools. The nature of its working is also dual, i.e., GUI and script based. This dual working ability makes it an easy-to-use tool for novices and for users looking to conduct more complex analyses.
Data analysis in dissertation – an important activity to perform. Data analysis provides you with clear insights into your research problem and helps you make informed decisions. However, for this to happen, you have to have command over several different data analysis tools. The top 7 tools are mentioned above, in which MATLAB, MS Excel, and SPSS are also included. So, read the information above and analyse the collected data effectively.