Overview of Quantitative Research Methods
Quantitative methods are different from qualitative methods in how observations are made. This is not the only difference, but it is the most basic one.
Before we start talking about quantitative methods. Let's briefly review and expand upon some basic things we have gone over.
We have been talking about how we generate knowledge through the scientific process.
And the basic process is the same regardless of whether or not we use qualitative or quantitative methods.
That is, we have to state or identify some question that needs to be answered.
Then, we have employ some type of method that allows us to make observations, which will allow us to answer our question. That is, the basic goal of the scientific development of knowledge.
So, on some levels quantitative research is very similar to qualitative research. However, the key difference is in how observations are made.
Before we go over the specific details of using quantitative methods, let's cover some background information first. Some of this information will be review and some of it will be new.
I Background Information about quantitative methods.
A. Primary goal of quantitative research.
The primary goal of quantitative research is to identify relationships among variables through statistical analysis.
Remember, we have already talked about what variables are.
1 Variables are simply characteristics along which humans and/or their behaviors vary. Variables vary along attributes. Now there are two kinds of variables that we will run across when doing quantitative research.
Independent variables are variables that are thought to cause or produce a change in other variables. In other words, a change in an independent variable leads to a change in another variable.
On the other hand, dependent variables are variables believed to be influenced by other variables. That is, changes in an dependent variable are thought to be due to a change in another variable. Dependent variables depend on other variables -- change in relation to other variables.
So, lets say we are studying similarity and attraction. That is, we want to know whether or not similarity leads to attraction.
In this example
The Independent variable is Similarity
The Dependent variable is Attraction
However, what is an independent and dependent variable can change from study to study. In other words, variables are defined by how they are used within the context of a given study.
So, in another study, we may be focusing on whether or not attraction leads to helping behavior.
This time around:
The Independent variable is Attraction
The Dependent variable helping behavior
2 Relationships
Relationships are patterns or associations that exist between two or more variables.
a. Causal relationships
Relationships can be causal: a change in one variable produces a change in another variable.
Three things necessary to identify a causal relationship between two variables.
1. Change in independent variable must occur before change in dependent variable.
For example, if I want to show that similarity leads to attraction, I must show that similarity exists before attraction.
2. Must show that as the independent variable changes, the dependent variable changes. Obviously, if I change one variable and the other variable doesn't change, then I don't have a causal relationship.
3. Must be certain that the change in one variable is really do the change in the other variable, and not any other factors.
B. Correlation
Relationships can also be correlational -- a change in one variable is associated with a change in the other variable.
In other words, two variables seem to change together, but one really isn't causing the other to change.
B Variables are measured
A quantitative approach involves measuring variables.
In short, quantitative research measuring variables by assigning numerical values to represent differences in attributes.
Remember that variables vary along attributes. So, measuring variables simply means that we assign numerical values to different attributes.
C Deterministic
When employing a quantitative perspective, we implicitly assume that factors or forces influence behavior.
In other words, one thing follows another. For example, how you did in high schools determines or influences, in part, how you will do in college. .
That is, our behavior is determined by other variables, factors, or forces.
This model also assumes that our behavior is determined by factors or influences that we may have little awareness or control over.
Qualitative research, on the other hand, is interested in the meaning people assign to events and actions while quantitative research is more interested in identifying the factors that influence how people react.
Now, this does not mean that people don't have free choice or free will. We clearly do have some amount of free will or choice, but also our behavior is to some degree constrained or determined by other factors.
D Probabilistic Model
The second problem people have with quantitative methods is their probabilistic nature.
Often we think of knowledge produced by quantitative methods as specific, law like explanations, when in fact it is based upon a probabilistic model.
A probabilistic model simply tries to identify general, broad patterns that exist -- not always concrete, absolute laws.
Probabilistic model attempts to identify general, broad patterns (nomoethetic) rather than specific, absolute, concrete explanations (idiographic).
Not trying to identify what will absolutely happen, but what is more likely than not likely to happen. For instance, how you did in high school will probably influence how you'll do in college -- this is the general pattern, it is more likely to happen than not happen. However, keep in mind, there are exceptions to the rule, but the rule does exist.
For example:
Lets say that we find that their is a relationship between similarity and attraction. That is, we find that the more similar people are to us the more attracted we will be to them. However, this does not mean that for every single person, under every single situation, that an increase in similarity will lead to attraction, rather it just means it is more likely to happen than not happen.
Try to keep these things in mind throughout
that rest of the quarter. You'll have a much better understanding
and easier time learning quantitative if you're able to keep this
background information in mind.