Facts and theories in scientific inquiry

¶ … Theories

Two attribution theories applied to marketing include the correspondent inference theory and self-perception theory. The first applies causal attribution to determine the nature of a customer's behavior based on behavioral cues. The cues are derived from a single behavior in a particular situation. Therefore, information on its generalizability can be inferred from the behavior (Wang, 2008). Self-perception theory operates on the premise that behavioral cues emerge from both the observer and the person being observed. Two sets of causal attribution are therefore possible and can be synthesized on the basis of both sets of observations.

Other theories include the brand personality dimensions framework, which operates to compare measured brand personalities, and the hierarchy of effects models, which help marketers to determine the effect of specific advertising techniques on consumers (Marketing Journal, 2005).

Both propositions and hypotheses are statements; the content of these statements, however, differ significantly. A proposition, for example states relationships among concepts. A proposition would explain a logical link between concepts by making a statement regarding a universal connection. This connection is far too general to test empirically. An example might be the link between being friendly in a classroom and loyal, happy students. This is, however, not testable by means of empirical testing (Zikmund et al., 2013).

Hypotheses, on the other hand, make far more specific statements in a formal way in order to explain an expected outcome. In other words, it is a type of "guess" about a probable result. In a teaching situation, this might relate to a specific teaching method that results in better reading test results than other teaching methods (Rao, 2012).

3. Concepts provide a generalized idea about a class of things. These things can be any object, attribute, event, or process that has been given a name. These concepts are highly abstract, offering names for abstract ideas within any subject field. Being abstract, no specific numerical values are attached to these concepts. In organizational theory, for example, leadership and morale are concepts. These do not have specific numeric values attached to them. Even in finance, specific, empirical values are not implied in concepts such as inflation or gross national product.

This is where the basic difference between "concept" and "variable" comes in. A variable is something that can take different numerical values. It is related to a concept in that it is its empirical assessment. Once differentiating numbers are therefore applied to concepts, they become variables.

4. The expression "there is nothing so practical as a good theory" concerns the interaction of theories with the practical observations they emerge from and explain. When creating a theory in marketing, for example, this theory is used as a basis for practical action. A good theory, in this way, supports effective actions for years and even decades. Hence, no good theory can, in truth be described as purely theoretical. A good theory must inform practice, which in turn can inform new theories. This constant interaction of theory and the practical world, as well as their continual influence on each other, means that a good theory is indeed practical. In response to the question, I therefore agree with Kurt Lewin's statement. Theories help us to understand reality. To accomplish that, theories must by nature be practical.

5. Spinoza's statement, in practical terms, simply means that research tends to be an on-going process. Theory formation and testing is by nature not only an intricate process, but also tends to be a flawed one. No scientist or academic can prove beyond a doubt that his or her created theory is absolutely and without a doubt correct. Indeed, new methods of investigation or new information that comes to light frequently prove existing theories false, which then have to be modified to fit the new observations. Only existing data, or facts, can be used to verify any given theory at any given time. Hence, when people believed the earth was flat and the center of the universe, this was based upon the existing data that could be observed at the time. Once this input changed, the theory became false. Although there was a concerted attempt to maintain the "facts" as they were, progress necessarily took over and presented the facts as they are recognized today. Another example of this is the nature of Pluto, first believed to be a planet. Theories on the nature of planets later proved this fact incorrect.