Full Answer Section

1. Correlational Research: Correlational research explores the relationship between two or more variables. It seeks to determine if there is an association and the strength and direction of that association. However, it does not establish cause-and-effect. For instance, a study might look at the correlation between study hours and exam scores or between income level and consumer spending.

2. Quasi-Experimental Research: This type attempts to establish cause-and-effect relationships between variables, similar to experimental research. However, it lacks the random assignment of participants to groups, which is a hallmark of true experiments. Researchers often use pre-existing groups. An example could be comparing the performance of students in two different classrooms using different teaching methods, where the students were not randomly assigned to the classrooms.

3. Experimental Research: Often considered the “gold standard” of quantitative research, experimental research rigorously investigates cause-and-effect relationships. Researchers manipulate one or more independent variables to determine their effect on a dependent variable while controlling for other extraneous variables. Participants are randomly assigned to different treatment groups (including a control group). A classic example is testing the effectiveness of a new drug by randomly assigning patients to receive the drug or a placebo.

Differentiating Between Basic and Applied Research

The primary difference between basic and applied research lies in their purpose and goals:

• Basic Research (also called fundamental or pure research):

  • Primary Goal: To expand the existing body of knowledge and understanding of fundamental principles and phenomena. It is driven by curiosity and the desire to explore and explain the world around us.
  • Focus: Often theoretical and may not have immediate practical applications. It seeks to answer questions like “How does this work?” or “What are the underlying mechanisms?”.
  • Examples: Investigating the structure of an atom, studying the principles of learning in humans, or exploring the nature of dark matter.

• Applied Research:

  • Primary Goal: To find practical solutions to specific problems or to address the immediate needs of society, organizations, or industries. It aims to apply existing knowledge to solve real-world issues.
  • Focus: Practical and solution-oriented. It seeks to answer questions like “How can we solve this problem?” or “How can we improve this process?”.
  • Examples: Developing a new marketing strategy for a product, testing the effectiveness of a new teaching method in a classroom, or finding ways to improve energy efficiency in buildings.

In essence, basic research lays the groundwork and expands our understanding, while applied research takes that understanding and uses it to create tangible solutions. Often, applied research builds upon the findings of basic research.

5 Approaches to Quantitative Research

While the four types above categorize the overall design, there are different approaches within quantitative research that guide the data collection and analysis process. Here are five common approaches:

1. Survey Research: This is a very common approach that involves collecting data from a sample of individuals using questionnaires or interviews. Surveys can be used for descriptive, correlational, or even quasi-experimental research designs. The goal is to gather information about attitudes, opinions, behaviors, or characteristics of a population.

2. Experimental Research: As described earlier as a type, it’s also a distinct approach focused on manipulating variables and establishing cause-and-effect in a controlled environment. This approach often involves pre-tests and post-tests, control groups, and treatment groups.

3. Correlational Research: Again, also a type, this approach specifically focuses on examining the statistical relationships between two or more variables. Researchers collect data on the variables of interest and use statistical techniques to determine the strength and direction of their association.

4. Causal-Comparative Research (Ex Post Facto Research): This approach aims to identify cause-and-effect relationships after the fact. Researchers compare groups that already differ on a particular characteristic or experience to determine possible causes or consequences. Since the independent variable is not manipulated, establishing causality is more challenging than in experimental research.

5. Secondary Data Analysis: This approach involves using existing data that was collected for another purpose. This can include government statistics, census data, health records, or data from previous research studies. Researchers analyze this data to answer new research questions. This approach can be cost-effective and time-saving but requires careful consideration of the data’s relevance and quality for the current research question.