In the realm of research and data collection, two vital statistical techniques come to the forefront: surveys and experiments.
These methodologies play distinct roles, with surveys focusing on descriptive research and experiments serving as a primary source of data in experimental studies.
This article aims to cover the differences between surveys and experiments, providing valuable insights into their respective characteristics.
Survey
In the realm of research, surveys serve as a powerful tool for gathering information about a specific variable of interest from individuals within a population.
A survey can take the form of a sample survey or a comprehensive census survey, both of which involve questioning informants on a particular subject. To ensure structured data collection, a formal questionnaire is prepared, presenting the questions in a predetermined sequence.
Through various means such as observation, direct communication via telephone, mail, or personal interviews, informants are probed about their behavior, attitudes, motivations, demographic profiles, and lifestyle characteristics.
Responses may be obtained verbally, in writing, or via computerized formats, depending on the chosen modality. This comprehensive approach enables researchers to obtain data that aligns with their research objectives.
Experiment:
Experiments, on the other hand, constitute a systematic and logically structured scientific procedure employed to test hypotheses and gain insights into specific factors under investigation.
These controlled experiments involve manipulating one or more independent variables while carefully measuring any resulting changes in one or more dependent variables.
To ensure accurate results, researchers also account for the influence of extraneous variables that may impact test units’ responses.
Conducted intentionally, experiments aim to observe and understand outcomes, demonstrate known facts, or discover new phenomena.
Drawing conclusions from the study group, researchers make inferences that extend beyond the sample to a larger population of interest.
By isolating the factor under scrutiny, experiments contribute significantly to our understanding of cause-and-effect relationships, particularly in the physical and natural sciences.
Survey vs. Experiment
Survey and experiment diverge on several grounds, which can be summarized as follows:
![](https://mimlearnovate.com/wp-content/uploads/2023/06/we-1-1024x779.jpg)
- Nature and Purpose: Surveys primarily serve descriptive research, aiming to explore possible relationships between data and unknown variables. In contrast, experiments are integral to experimental research, seeking to establish and test hypotheses through isolating specific factors.
- Definition: A survey is a method of gathering information from the general public about a variable under study. Experiment refers to a scientific method in which the factor under study is isolated in order to test a hypothesis.
- Sample Sizes: Surveys often require larger sample sizes, compensating for potentially low response rates, especially when utilizing mailed questionnaires. Conversely, experiments generally rely on relatively smaller samples to achieve their research objectives.
- Applicability: Surveys find suitability in social and behavioral sciences, whereas experiments occupy a critical position in the realms of physical and natural sciences.
- Research Context: Surveys epitomize field research, conducted outside of laboratories and workplaces, capturing data in real-world settings. Experiments, however, epitomize laboratory research, where controlled conditions and scientific tools enable precise observations.
- Data Collection: Surveys adopt diverse methods such as observation, interviews, questionnaires, and case studies to collect data directly from participants. Conversely, experiments derive data from repeated readings or observations of the experimental conditions.
Aspect | Surveys | Experiments |
---|---|---|
Definition | A survey is a method of gathering information from the general public about a variable under study. | Experiment refers to a scientific method in which the factor under study is isolated in order to test a hypothesis. |
Purpose of Research | Descriptive | Experimental |
Sample Sizes | Large | Relatively small |
Suitable Research Domains | Social and Behavioral Sciences | Physical and Natural Sciences |
Data | Deals with secondary data. | Deals with primary data |
Research Example | Field Research | Laboratory Research |
Data Collection Methods | Observation, Interview, Questionnaire, Case Study etc. | Multiple experiment readings |
Primary Analysis | Correlation | Causation |
Cost | Less cost | Higher cost |
Strengths | Gather large amounts of data | Establish cause-and-effect relationships |
Limitations | Limited generalizability, time, resources | Artificial environment, ethical concerns |
Conclusion
To summarize, while surveys aim to uncover and control relationships between variables in social and business research, experiments focus on determining cause-and-effect relationships and achieving high internal validity.
Surveys boast the ability to gather substantial amounts of data from representative samples and generalize their findings to larger populations.
Conversely, experiments offer the advantage of establishing causal links, enabling the manipulation and control of variables within controlled environments.
However, experiments may face limitations such as artificiality, ethical considerations, limited generalizability, and resource requirements.
Researchers must carefully consider these strengths and limitations when deciding on the most appropriate methodology for their research objectives.
Other articles
Please read through some of our other articles with examples and explanations if you’d like to learn more about research methodology.
Comparision
- Basic and Applied Research
- Cross-Sectional vs Longitudinal Studies
- Survey vs Questionnaire
- Open Ended vs Closed Ended Questions
- Experimental and Non-Experimental Research
- Inductive vs Deductive Approach
- Null and Alternative Hypothesis
- Reliability vs Validity
- Population vs Sample
- Conceptual Framework and Theoretical Framework
- Bibliography and Reference
- Stratified vs Cluster Sampling
- Sampling Error vs Sampling Bias
- Internal Validity vs External Validity
- Full-Scale, Laboratory-Scale and Pilot-Scale Studies
- Plagiarism and Paraphrasing
- Research Methodology Vs. Research Method
- Mediator and Moderator
- Type I vs Type II error
- Descriptive and Inferential Statistics
- Microsoft Excel and SPSS
- Parametric and Non-Parametric Test
Comparision
- Independent vs. Dependent Variable – MIM Learnovate
- Research Article and Research Paper
- Proposition and Hypothesis
- Principal Component Analysis and Partial Least Squares
- Academic Research vs Industry Research
- Clinical Research vs Lab Research
- Research Lab and Hospital Lab
- Thesis Statement and Research Question
- Quantitative Researchers vs. Quantitative Traders
- Premise, Hypothesis and Supposition
- Survey Vs Experiment
- Hypothesis and Theory
- Independent vs. Dependent Variable
- APA vs. MLA
- Ghost Authorship vs. Gift Authorship
Research
- Research Methods
- Quantitative Research
- Qualitative Research
- Case Study Research
- Survey Research
- Conclusive Research
- Descriptive Research
- Cross-Sectional Research
- Theoretical Framework
- Conceptual Framework
- Triangulation
- Grounded Theory
- Quasi-Experimental Design
- Mixed Method
- Correlational Research
- Randomized Controlled Trial
- Stratified Sampling
- Ethnography
- Ghost Authorship
- Secondary Data Collection
- Primary Data Collection
- Ex-Post-Facto
Research
- Table of Contents
- Dissertation Topic
- Synopsis
- Thesis Statement
- Research Proposal
- Research Questions
- Research Problem
- Research Gap
- Types of Research Gaps
- Variables
- Operationalization of Variables
- Literature Review
- Research Hypothesis
- Questionnaire
- Abstract
- Validity
- Reliability
- Measurement of Scale
- Sampling Techniques
- Acknowledgements
Statistics