Quantitative Research Designs

Research Designs
1. Introduction
2. Types of Research Designs
Research Designs can be categories into quantitative research designs and qualitative research designs or mix method research design.
Types of quantitative research designs
Quantitative research designs tend to be more fixed and deductive, with variables and hypotheses clearly defined in advance of data collection. Quantitative research example, if you want to test the effectiveness of an online teaching method, a quantitative approach is most suitable. You can use this type of research to measure learning outcomes like grades and test scores. Quantitative research designs can be split into four main types.
• Experimental and quasi-experimental designs allow you to test cause-and-effect relationships
• Descriptive and correlational designs allow you to measure variables and describe relationships between them.
Following research design categories in quantitative research:
2.1 Descriptive research design: This quantitative research design is applied where the aim is to identify characteristics, frequencies, trends, and categories. It may not often begin with a hypothesis. The basis of this research type is a description of an identified variable. This research design type describes the “what,” “when,” “where,” or “how” of phenomena (but not the “why”).
Example: A study on the different income levels of people who use nutritional supplements regularly.
2.2 Correlational research design: Correlation reflects the strength and/or direction of the relationship among variables. The direction of a correlation can be positive or negative. Correlational research design helps researchers establish a relationship between two variables without the researcher controlling any of them.
Example: An example of correlational research design could be studying the correlation between time spent watching crime shows and aggressive behavior in teenagers.
2.3 Diagnostic research design: In diagnostic design, the researcher aims to understand the underlying cause of a specific topic or phenomenon (usually an area of improvement) and find the most effective solution. In simpler terms, a researcher seeks an accurate “diagnosis” of a problem and identifies a solution.
Example: A researcher analyzing customer feedback and reviews to identify areas where an app can be improved.
2.4 Explanatory research design: In explanatory research design, a researcher uses their ideas and thoughts on a topic to explore their theories in more depth. This design is used to explore a phenomenon when limited information is available. It can help increase current understanding of unexplored aspects of a subject. It is thus a kind of “starting point” for future research.
Example: Formulating hypotheses to guide future studies on delaying school start times for better mental health in teenagers.
2.5 Causal research design: This can be considered a type of explanatory research. Causal research design seeks to define a cause and effect in its data. The researcher does not use a randomly chosen control group but naturally or pre-existing groupings. Importantly, the researcher does not manipulate the independent variable.
Example: Comparing school dropout levels and possible bullying events.
2.6 Experimental research design: This research design is used to study causal relationships. One or more independent variables are manipulated, and their effect on one or more dependent variables is measured. Example: Determining the efficacy of a new vaccine plan for influenza.
2.6.1 Strengths: Establishes cause-and-effect relationships, high internal validity.
2.6.2 Limitations: May not be feasible or ethical in all situations.

2.6 Survey Design
This design involves collecting data through self-report measures, such as questionnaires or interviews. Survey designs are useful for studying attitudes, opinions, and behaviors.
Subtypes
1. Cross-Sectional Survey: Data is collected at one point in time.
2. Longitudinal Survey: Data is collected over a period of time.
Subtypes
i. Cohort Study: Follows a group of individuals over time.
ii. Panel Study: Collects data from the same participants at multiple points in time.
iii. Trend Study: Examines trends over time.
Strengths: Allows for examination of changes over time.
Limitations: May be time-consuming and expensive.
3. Panel Survey: Same participants are surveyed at multiple points in time.
Strengths: Allows for collection of large amounts of data, can be cost-effective.
Limitations: May be subject to bias, relies on self-report data.

Видео Quantitative Research Designs канала Think vista with Dr Aqeel and Nagina khan