Research project writing has taken a new dimension in almost all higher institutions around the globe. Researchers today are looking for the best ways to solve problems surrounding the aims and objectives of research project. The reason why I’m writing this article is educate undergraduate students on the variations in data analysis; be it secondary data analysis or primary data analysis.
Let me first of all intimate you guys on what primary data and secondary data is all about. Primary data as regard project topics is a kind of raw data which is usually gotten from the distribution of questionnaires or interview. Here you have to quantify it to become secondary data. We can see the use of primary data for education project topics and other related education project topics like adult education, biology education and economics education etc. All these departments make use of primary data for data analysis.
The secondary data in the light of project writing are data that are already processed and ready to use. Most of this data are seen from cenbank.org, Nigeria bureau of statistics and worldbank.org
Unlike the education project topics and other related departments; the economics project topics, accounting project topics and banking and finance project topics always make use of secondary data unless demanded otherwise by the project supervisor.
Now let me tell you why secondary data analysis is becoming more efficient than the primary data analysis. The secondary analysis always shows the nature and the extent of the relationship between two variables while the primary data will only show the existence of a relationship.
For example consider the project topic: effect of oil tax revenue on the Nigeria economy
We can see the variables here are oil tax revenue and Nigeria economy. If we use primary data and then select a particular statistical tool like chi-square, we will not be able to know whether the effect is positive or negative. But when it comes to secondary data analysis still on the above topic; we will look for the statistical bulletin that contains the determinants of oil tax revenue and the determinant of Nigeria economy. Basically the statistical tool used here is regression. At the end of the data analysis you will see the result of the effect (whether positive or negative) of oil tax revenue on the Nigeria economy. To know about research project writing and data analysis click here>>