Quantitative research is a type of research methodology that involves a collection of numerical data to answer a specific research question. Taking this definition one step further Christiansen goes on to note that quantitative research is a descriptive type of research where the goal is to attempt to provide an accurate description or picture of a particular situation or phenomenon. Rather than utilizing the cause and effect relationships that are common to quantitative methodologies, qualitative investigations attempt to identify variables that exist in a given situation and, at times, to describe the relationship that exists between these variables. To accomplish this task statistical data is typically utilized.
With a basic understanding of quantitative research clearly elucidated, it is now possible to consider the specific methodologies that are utilized in this context. Through a careful consideration of the various methods that utilize quantitative research it will be possible to demonstrate not only the differences between quantitative and qualitative research but also the importance of this type of research to scholarly investigation. Although statistical data is a linchpin of qualitative research methods, it is evident that there are a myriad of ways in which to acquire data.
Defining the basic context of the correlational study you may observe that this method involves measuring two specific variables and attempting to quantify the relationship that exists between these variables. Correlational studies are important because they demonstrate the specific relationships that exist between two variables. If A can be correlated with B, other variables correlated with B may also have relationships to A. Thus, by delineating the specific relationships that exist between two variables researchers can make a number of predictions about the impact of other variables in the same or similar situation.
What is perhaps this interesting about the correlational study is that it provides a mechanism for ensuring internal validity. Fraenkel and Wallen go on to argue that a correlational study poses no possibility of manipulating implementers. As such, the results obtained in this context can be stringently verified with regard to statistical analysis. For this reason, the correlational study provides one of the most salient means for the quantification of data in a given experiment. The ability to statistically quantify results serves as the basis for promoting the integrity of data collected through this process.
Ex-post Facto Study
The ex-post facto study is unique because it requires the investigator to determine the specific variables for analysis after the research has been completed. According to Ary and Suen (1989) the ex-post facto study utilizes a sample population that is similar to that of the general population. In this context, a similar variable is identified that links the subject population together. Subjects are broken into various groups and exposed to the same experimental conditions. Observations are made by the researcher to discern if there are differences in behavior based upon the notable differences among individuals in the population. Through this process, the researcher is able to investigate subjects in a naturalistic environment and to draw conclusions about what specific variables will influence behavior and outcomes.
A longitudinal studies makes the following observations, Longitudinal studies investigate developmental changes that take place at the time. The longitudinal study involves choosing a single group of participants and measuring them repeatedly at selected time intervals to note the changes that occur over time in the specified characteristics. The longitudinal study provides a salient means for collecting data with respect to the age and development of the subject. In particular, longitudinal studies often involve children, as researchers seek to discern how specific variables change through the course of growth and development. In this context, the longitudinal approach can provide marked insight into the process of change.
Meta-Analysis can be used to synthesize the large volume of data describing numerous independent variables and their correlations with reference accuracy. Meta-analysis enables researchers to utilize information from past studies to better understand the specific variables that impact a subject. Typically, meta-analyses are undertaken for the purpose of synthesizing extensive amounts of work on a particular subject. Utilizing the data that has been collected in previous investigations, researchers can synthesize information to better understand the subject and to develop new research methodologies that specifically target the gaps in information that are identified through the process of meta-analysis.
The survey is defined as a method of collecting standardized information by interviewing a representative sample of some population. Although the survey is one of the most popular methods for quantitative investigation, over the course of the last several years, the integrity of this method has been questioned. In most cases surveys involve direct contact with the population under investigation. Although well-established survey methods can be utilized for investigation, in many cases researchers seeking to understand a new facet of a particular population will develop a survey whose validity and reliability have not been proven. Even though specific methods for the development of surveys have been presented in the literature, utilizing a survey that has not been validated can serve as the basis for corrupting the integrity of data collection.
Christensen, L.B. (2001). Experimental Methodology (8th Ed). Boston, MA: Allyn and Bacon.
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