Statistical Data Analysis in Social Science Research
Dear Steemians,
I will present here a series of tutorials about how to analyse the statistical data that you have collected during your project in any social science field, such as sociology, anthropology, psychology, economics or education.
Data analysis is not the only part of any research project. However, it is the most important part that shows that the hypothesis that you have formulated and for which you have collected the data, is supported by the results of the data.
Researchers formulate their hypothesis after first carefully planning their research project. As a researcher/ statistician myself, I have the following tips before starting collecting the data for your project.
Careful planning of the research project
You should have the knowledge of already-existing theories and research about the topic that you are going to investigate. You should clearly know the purpose of your study and that, what goal you will achieve and why this is important. What will it add to the existing research.
Foresightedness and foreseeing
You should have the ability to anticipate potential issues or hurdles that you may face during the data collection process. You can avoid most of these problems if you have the proper knowledge of what variables you would need to answer your research questions. Suppose, you want to investigate the affect of physical activity on mood. For this you may need to construct variables such as (i) physical activity, (ii) severity of depression, (iii) age of the participants, (iv) gender, and you may also want to control the affect of certain variables such as smoking, working hours, sleep time and duration etc.
Once you have the knowledge of what you would assess during your project, you are then ready to start collecting your data.
Getting organized
As you advance with your research, you would have hundreds of research articles about different aspects of your studies. With the example above about mood and physical activity, you would need articles on mood, depression, and physical activity, and on the association of these variables on gender and age, for example; so you really need to be organized right from the start. Make separate folders of the articles on different topics. You would need these articles in print and digitally. Moreover, when you run your analysis on a data analysis software, you also have to organize the output files of different variables. For example, with the software called SPSS, R, or STATA, you not only need to save the files where you have entered your raw data, but also the syntax and outfiles. Syntax files, especially, are the most important ones as you would need them if you want to re-run the analysis with minor changes. If you fail to do keep these records, you would not be able to publish your research work in time; further, you wouldn't be able to answer the questions raised by the reviewers at the time of submitting your work to a scientific journal.
Spend time with yourself
Research becomes hectic at times. Therefore, you need plenty of time to spend with yourself. Close all the files, switch off the phone, computer, go offline and spend some time in nature. This is what I do!
These are the things I learned during my research. I hope these tips will be of some help to you.
I see you in my next series of posts about how to analyse data in SPSS.