Quantitative methods, including statistical analysis, can allow researchers to investigate large datasets and identify patterns or trends, such as to predict election outcomes.
Oppositely, qualitative methods deal with deep analysis of smaller sets of data such as interviews, documents, and case studies.
Then, in 1919, the first political science journal utilizing quantitative methods was published, which helped grow the development of the field.
[3] This led to the first major phase in the 1920s, where scholars such as Charles Merriam showcased the importance of incorporating statistics into various forms of analysis.
In the 1970s, there was a shift towards creating original sets of data to measure specific abstract political concepts such as ideology and representation.
[3] Researchers and scholars used innovative approaches including content analysis and event counts to widen the analytical capabilities and answer previous unanswerable questions.
A major development that occurred during this period was the use of advanced statistical methods from other fields, such as regression models, time series analysis, and scaling techniques.
[8] Most of those data sets that political campaigns use need to be sorted through, or applied to statistics in order to achieve accurate outcomes and forecasts for probabilities based on the datasets that were stored within the database.
[15] Politicians often use rhetoric that is believed to be supported by a factual basis, but often times the specific data or analysis that the candidates are referencing has been taken out of context in some regard.