Analytical research is an integral part of any political science research. Knowing the different methods through which political researchers are able to analyze their research is crucial for anyone looking to develop new insight.
For hundreds of years, political theorists, judges, lawyers, and legal scholars, have all worked to create new theories and means for understanding the ever-developing institutions that govern us.. Political science research influences real-world decision-making - from this year’s military spending budget, down to the amount of fees the post office is allowed to charge to send a letter.
There are a variety of unique tools and methodologies employed by researchers trying to tackle problems in the real-world. Today we will go over the essentials of political research, and highlight the many unique ways researchers can gather and analyze data.
Political science research is typically concerned with the theory and practice of governing, lawmaking, and politicking. Political scientists, like researchers in other disciplines, utilize a number of different methods and tools to conduct experiments, and gather new insights about a particular issue or phenomenon.
Quantitative data analysis is concerned with measuring the raw figures and numbers. This form of data analysis uses statistical models and math, to develop new theories about the world around us.
Quantitative analysis is a form of descriptive statistics; meaning they are used to quantify the most basic features of a data set. Quantitative data can either be discrete (having to do with a particular set of numbers) or continuous - meaning that any numeric value could have a potential fit.
Examples of quantitative data collection most commonly involve some kind of political surveying or polling, and is concerned with gathering information such as:
These are all characteristics that can be easily picked apart and quantified using numerical data. They tell us how much of something there is in any given topic - allowing us to perform necessary calculations during our analysis.
Conversely, qualitative data analysis is concerned with identifying and exploring those types of qualities that cannot be easily defined by numbers and figures. Qualitative data is most often composed of observations: descriptions of behaviors and phenomenon that cannot be quantified by numbers.
Qualitative data analysis can be thought of as looking at the “how” or “why” of a particular issue, whereas quantitative data captures the “what”. These observations are invaluable to researchers, as they assign reason and motivation behind an action. Knowing what motivates someone to make a particular action is what drives the majority of political research projects today.
Qualitative data can be broken down into three distinct types:
Ordinal data exists on a ranging scale, and is one of the most prevalent types of questions found in a traditional survey. Questions that ask participants to share answers based on a sliding scale (such as “very unlikely” to “very likely”) are a common form of ordinal data collection.
Binary data is represented numerically, and is most often used in the creation of statistical models. These models can be used to track the likelihood of an individual to make a certain choice, among other things.
Nominal data is used to label a subject without the use of numerical figures. These include multiple-choice political survey responses, or cases where subjects are allowed to self-sort into a particular group.
Game Theory is a model for studying the decision-making process that goes on behind nearly every social interaction. Strategy, cost-benefit analysis, and optimal decision-making are all integral parts of the game theory model.
Researchers often use game theory models in order to better understand how individual actors come to a decision when faced with competition or consequence. The Prisoner’s Dilemma - where two convicts are tasked with choosing whether or not to inform on the other, therefore risking jail time, is a classic example of game theory in action.
Historical analysis is a hugely important tool for political science researchers, as it enables them to present history as more than just a series of events that happened in succession. Overcoming this traditional and simplistic way of stating history - like the way you might see it described in a children’s textbook - is crucial for researchers looking to derive new insights from their political analysis.
Researchers can draw upon historical inferences from a number of sources including historical texts, films, as well as first and second-hand accounts of events. Researchers will often build off of the works of prior authors in order to develop their own theories and outlooks.
Historical analysis is a common and very effective model for deriving new insights from history. For example, judges often make determinations on matters of law by using historical and legal precedence to inform their decision-making.
Scenarios are a flexible tool that can be used to develop models; models that can be used to drive everything from policy making down to law enforcement.
Scenarios can be as vast and unspecific - or as calculated and precise - as you need them to be. Social scientists often develop broad scenarios centered around a specific issue or problem they want to explore. These theoretical scenarios are then used to answer key questions like:
Theoretical scenarios are a cost-effective way for researchers to predict and forecast changing phenomena. They can also be used to argue for or against a particular course of action; enabling researchers to build up support for their conclusions, turning them into real-world action.
Analytical research is an integral part of any political science research. Knowing the different methods through which political researchers are able to analyze their research is crucial for anyone looking to develop new insight.
For more information on the steps of the research process and data analysis, please visit our Helpfull research guide.
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