Scientific Method

Probability

Animals have little concept of time. They have limited problem solving ability (compared to human thinking). What we are about to consider now is the human concept involved in studying relationships and other attributes over time to develop a human knowledge that can be used to predict outcomes, behaviors, and events occurring over time. This is at the heart of scientific methodology, a methodology unique to human reasoning. With this, we might figure out a cure for cancer, the common cold, or viruses such as HIV. Animals do not possess such thinking capabilities.

So far we have concentrated mostly on deductive reasoning. This consisted in putting things in categories or pigeon holes. Everything has its proper "fit."

 Deductive reasoning is called á priori reasoning

In inductive reasoning, our knowledge becomes more approximate. We are more interested in cause and effect. There are two sides to this coin:
• Our knowledge is concerned that we have the proper cause for the effect
• Our knowledge has the proper effect, given the perceived causes.

 Inductive reasoning is called á posteriori reasoning

We first introduce "uncertainty" in our knowledge, and we call this uncertainty "probability." Thus we have probabilistic causal hypotheses and probabilistic effectual hypotheses.

Now we test the correlation between cause and effect. We might exclude some causes á priori. This generates what is called "exception fallacy."

We can measure behaviors over time. We can measure occurrences of a particular attribute over time. In this way, we gain a knowledge of the makeup of these attributes, give certain states or environments.

This process involves two types of variables. We have to control on variable so that we know for sure (certainty) the characteristic makeup and attributes. The dependent variable is the one that "responds" to what it is exposed to in the test. This is the one we are measuring. It "depends" on what other variables are introduced.

The independent variables are the ones that we control. This way, the scientist knows what he has introduced. This is his "certainty." The dependent variable is the "uncertainty" he hopes to measure to construct a theory (going from observation to theory - see chart below).

We are dealing with methodology here rather than epistemology. Epistemology is a term from the Greek for knowledge. While scientific methodology is concerned about knowledge, too, positivists would tend to reject more subjective concepts of reality, choosing to discount all except what can be measured.

Further, we don't mean to imply that only the measurable á posteriori type of knowledge involves probability - both types do as the table below indicates:

 A Priori Probability A Posteriori Probability Mathematical Empirical Independent of Events Dependent on Events Logical Scientific Statistical Experimental

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