What is Quantitative Research?
Quantitative research collects numerical and/or categorical data to explain, predict and/or control phenomena of interest. Quantitative statistical methods are used to analyze the data. When the data has been collected from a sample, it allows the results of the study to be generalized to a larger population. Studies can take the form of descriptive research, correlational research, or randomized-comparative research.
The Steps toward Quantitative Research Study
"It is better to have an approximate answer to the right question than an exact answer to the wrong one." - John Tukey
A well-defined research question is imperative for any study. What characterizes a good research question?
An example of "Poor Research Question": Are university faculty depressed?
An example of "Better Research Question": Does depression level among university faculty differ based on their gender, departmental affiliation, and tenure status, after controlling for marital status and life satisfaction?
This is a critical summary of relevant research on the topic of interest. To identify pertinent studies, researchers should review periodicals, online journals and books. Prior studies can be helpful in identifying appropriate data collection methods, sample survey instruments, proper statistical analysis and experimental design, as well as directions for future research. Below is a link to helpful online research tools available on the UVU Library's website:
The methodology section should clearly explain how the study is to be carried out. It should include:
Data collection process – How is the data to be collected? Is a survey being handed out? Were units randomly selected from a larger population?
Definition of variables – How are the variables defined and measured?
Some variables are easily defined and measured. For example, if we want to measure someone's height we use a tape measure. If we want to measure college-readiness we can use the SAT. However, many variables are difficult to define, let alone measure. For example, how do we define depression? Once it has been defined, how do we measure depression? Quantitative research is still flexible enough to handle these types of variables, but we need to consider the reliability and validity of our instruments being used. A thorough review of the literature is important here to identify a measuring instrument with demonstrated reliability and validity.
What type of statistical analysis will be used? Is it a correlational study or a randomized comparative study where subjects are randomly assigned to different treatments? Anytime human subjects are involved, researchers must go through the Institutional Review Board. (http://www.uvu.edu/irb/).
Data Analysis and Interpretation
Summarize the results of your study. Be sure to discuss the results in the context of your research question. Discuss whether or not the results were statistically significant and include p-values. For statistically significant results, include confidence intervals to measure the magnitude as well. Include tables and graphs where appropriate.
Discuss how your study answers the research question. Also be sure to include any limitations in the study. For example, the data may not have been collected as a random sample and therefore it is difficult to generalize the results of your study to a larger population. Maybe the study was a correlational study so establishing a cause-and-effect relationship between the independent and dependent variables is difficult. Finally, include directions for future research. Most studies, even when they successfully answer the research question, raise even more que