Theories are a way of explaining things. They consist of systemic sets of statements intended to explain something. Theories go hand in hand with paradigms, which provide us with a certain perspective for which to view reality. Theories in the social sciences can be either idiographic (attempting to provide a complete explanation of a small set of observations) or nomothetic (attempting to provide at least a partial explanation for a broad range of observations).
The parts that make up a theory
In order to produce a theory, you must first have made some observations. Furthermore, these observations must be factual. If you have enough of these factual observations, then you might be able to group them together to come up with a law. In order for something to be a law, it must occur universally (not just in specific situations) and must be testable and repeatable. With that being said, there aren't any "laws" in the social sciences due to the fact that the social sciences are much more complex than other sciences. Human beings behave differently under different conditions, and so there never really is a universal law that could help us predict exactly what they'll do. There may not be any laws in the social sciences, but there are many patterns which are predictable to a certain degree (not as predictable as the "hard" sciences).
We use concepts in order to communicate theories and patterns between variables. Concepts encapsulate complex phenomenon into one word or term. For example, "racism" is a concept with a broad range of phenomena contained within it (hate, bigotry, conflict, xenophobia, etc). A concept is basically an abstract term to represent some category of phenomena. Politics, money, race, gender, economy, etc, are all examples of concepts. When using concepts, it's important to clearly define what you are referring to within that concept in order to avoid ambiguity.
A theory of race could ask what is it that constitutes the idea of race. A theory on the income inequality could present an explanation as to what's causing it, and so on. In order to generate these theories you will need to use concepts, and furthermore, you'll need to use variables. Variables are measurable concepts with which we can change. We measure the change in variables in order to find a correlation, or a pattern, between the two. This is also called a hypothesis. For example, stating that: "when taxes decrease income inequality will decrease." This is a hypothesis, which contains two measurable variables and an expectation as to how they'll be related.
The scientific model
The three main components of the scientific model are theory, operationalization, and observation.
The theory is where you derive your hypothesis from. For example, if your theory is that income inequality rises whenever capitalism is left unregulated then you look for specific situations which prove your theory. Every hypothesis that you empirically test can help either support or refute a theory. Finding evidence in support of a theory strengthens that theory and encourages others to adopt it. Finding evidence to contradict a theory does the opposite.
Furthermore, once we've clearly defined our variables, we need to figure out how to measure them. Operationalization basically means figuring out how our research will operate when measuring things we think will be important to measure. Once we have both clearly defined our measurable variables, and exactly how we will measure them, we have come up with an operational definition.
Once we've come up with a testable hypothesis (a hypothesis which can be disproved), and operational definitions of our variables, we must now begin to observe. That is, we must look at, and measure, the things we said we were going to. You must also make sure to be as unobtrusive with your observations as possible. Make sure that whatever your observing isn't merely happening because of the way you're observing it.
When working with a hypothesis, we can either start our research with an already established theory or we can simply start observing and formulate a hypothesis and theory after observations. Deductive research is the first-mentioned method, in which we start with a theory and test a hypothesis in order to tear it down or make it more credible. In deductive research, you begin with an expectation. Inductive research, however, has no expectations nor any theories to back it. For this reason, inductive research is often exploratory. It works simply by collecting data, analyzing it, finding patterns, then building hypotheses which could support a new theory.
Conclusion
These are many ways to build a hypothesis. You don't necessarily need to come to a hypothesis this way. You could find your hypothesis with a mixture of inductive and deductive methods, for example. Using a deductive method helps you keep on an "established" track in which you have some guidance from previous research and ideas. However, the inductive method helps if you're looking to produce new theories, and maybe even a paradigm shift (someday). The inductive method also means that there is more risk for you due to the fact that there will be little support for these findings when they happen to contradict an established theory or paradigm. However you decide to engage in research, make sure you always work with determination and a good understanding of the existing literature.
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