Hello PhD researchers! Have you collected your research data, or are you about to finish this process? Okay. You are about the finish the process and want to know how to work on statistical analysis for thesis data beforehand. No worries, you have done a great job, and you have come to the right place for the required information. First of all, you should know that performing a statistical analysis is not a child’s play. To perform a good analysis and obtain concrete results, you must know the steps involved in it.
However, there are many PhD researchers who delve into the process of statistical analysis for thesis data without knowing the steps involved. Such researchers face difficulty once they start the analysis. So, to minimise the chances of errors and challenges, in today’s article, we will unearth the 7-step effective guide to work on statistical analysis. So, let’s get started with the topic straight away.
7-step guide for PhD researchers to perform statistical analysis
Statistical analysis is a step-by-step process. Each stage of statistical analysis for thesis data requires different skills and know-how. To get meaningful insights into your data and interpret it correctly, you, as a researcher, must have a grip on all the steps involved. However, a brief description of the top 7 steps involved in the analysis is as follows:
Define the question
The first step in any kind of analysis is to define your objective. In statistical analysis terms, it is called a “problem statement.” So, start the analysis by asking yourself: “what problem am I going to solve by doing this analysis?” Answering this question might seem straightforward, but it is the trickiest question. As the thesis data analyst, you must go deep into the problem and define the question.
Collecting the data
Once you have established your objective, the next step is to collect the data for your statistical analysis. Based on the research design, your data can either be quantitative or qualitative. Quantitative is the data which is in numerical form, and qualitative data is one which consists of words, expressions, and statements. Whatever your data type is, collect the required data using the right method.
Clean the data
Step no. 3 is about cleaning the data and getting it ready for analysis. This step is crucial to make sure that you are working with high-quality data which is free from any kind of errors. The key data cleaning tasks include:
- Removing major errors from the data, duplicate entries, and outliners
- Extracting irrelevant observations that are not relevant to the research problem
- Bringing a structure to the data
Cleaning the data is important because if you do not clean it, your analysis results may get impacted. If you feel that you do not have the skills to clean the data, you can search for thesis writing services to clean the data for you.
Choose the analysis method
Step no. 4 is the most important step in the entire statistical analysis for thesis data process. Once you have cleaned your data, it is ready for analysis. The analysis method for the data depends on its type. Qualitative data employs different methods, and quantitative data have different methods. So, decide and choose one analysis method based on your data type.
Start analysing the data
At last, the step has arrived which you were waiting for. After selecting one particular research method, read its procedures and start analysing the data. In your analysis, make sure that you get the patterns and themes right. The reason is that if you employ the wrong analysis technique, all your results can be ruined within a matter of time.
Interpreting the results
Up to this step, you have analysed the collected data. The next step is to interpret the results and interpret them right. By looking at the results of the analysis, unearth any themes and patterns that you see in it. Doing this is necessary because it helps the decision-makers decide about the possible solutions to the researched problem.
Share your results
Congratulations, you have finished the statistical analysis for thesis data. The only step now remains is the sharing of data with the concerned audience. If your research was funded, you are liable to share all the data with major stakeholders. If you are doing the research as an individual project, write a dissertation and share your data this way.
Conclusively, working on statistical analysis for thesis is not an easy task. It requires you to follow a step-by-step process and have knowledge of different analysis methods. The 7-step guide given above can help you a lot in carrying out a successful statistical analysis. Therefore, pay attention to each step mentioned above and choose your analysis method carefully.