Experiment vs Observational Study: Similarities & Differences

An experiment involves the deliberate manipulation of variables to observe their effect, while an observational study involves collecting data without interfering with the subjects or variables under study.

This article will explore both, but let’s start with some quick explanations:

• Experimental Study: An experiment is a research design wherein an investigator manipulates one or more variables to establish a cause-effect relationship (Tan, 2022). For example, a pharmaceutical company may conduct an experiment to find out if a new medicine for diabetes is effective by administering it to a selected group (experimental group), while not administering it to another group (control group).
• Observational Study: An observational study is a type of research wherein the researcher observes characteristics and measures variables of interest in a subset of a population, but does not manipulate or intervene (Atkinson et al., 2021). An example may be a sociologist who conducts a cross-sectional survey of the population to determine health disparities across different income groups. 

Experiment vs Observational Study

1. Experiment

An experiment is a research method characterized by a high degree of experimental control exerted by the researcher. In the context of academia, it allows for the testing of causal hypotheses (Privitera, 2022).

When conducting an experiment, the researcher first formulates a hypothesis, which is a predictive statement about the potential relationship between at least two variables.

For instance, a psychologist may want to test the hypothesis that participation in physical exercise (independent variable) improves the cognitive abilities (dependent variable) of the elderly.

In an experiment, the researcher manipulates the independent variable(s) and then observes the effects on the dependent variable(s). This method of research involves two or more comparison groups—an experimental group that is subjected to the variable being tested and a control group that is not (Sampselle, 2012).

For instance, in the physical exercise study noted above, the psychologist would administer a physical exercise regime to an experimental group of elderly people, while a control group would continue with their usual lifestyle activities.

One of the unique features of an experiment is random assignment. Participants are randomly allocated to either the experimental or control groups to ensure that every participant has an equal chance of being in either group. This reduces the risk of confounding variables and increases the likelihood that the results are attributable to the independent variable rather than another factor (Eich, 2014).

For instance, in the physical exercise example, the psychologist would randomly assign participants to the experimental or control group to reduce the potential impact of external variables such as diet or sleep patterns.

Examples

1. Impacts of Films on Happiness: A psychologist might create an experimental study where she shows participants either a happy, sad, or neutral film (independent variable) then measures their mood afterward (dependent variable). Participants would be randomly assigned to one of the three film conditions.

2. Impacts of Exercise on Weight Loss: In a fitness study, a trainer could investigate the impact of a high-intensity interval training (HIIT) program on weight loss. Half of the participants in the study are randomly selected to follow the HIIT program (experimental group), while the others follow a standard exercise routine (control group).

3. Impacts of Veganism on Cholesterol Levels: A nutritional experimenter could study the effects of a particular diet, such as veganism, on cholesterol levels. The chosen population gets assigned either to adopt a vegan diet (experimental group) or stick to their usual diet (control group) for a specific period, after which cholesterol levels are measured.

Read More: Examples of Random Assignment

Strengths and Weaknesses

Strengths of Experimental Research	Weaknesses of Experimental Research
1. Able to establish cause-and-effect relationships due to direct manipulation of variables.	1. Potential lack of ecological validity: results may not apply to real-world scenarios due to the artificial, controlled environment.
2. High level of control reduces the influence of confounding variables.	2. Ethical constraints may limit the types of manipulations possible.
3. Replicable if well-documented, enabling others to validate or challenge results.	3. Can be costly and time-consuming to implement and control all variables.

Read More: Experimental Research Examples

2. Observational Study

Observational research is a non-experimental research method in which the researcher merely observes the subjects and notes behaviors or responses that occur (Ary et al., 2018).

This approach is unintrusive in that there is no manipulation or control exerted by the researcher. For instance, a researcher could study the relationships between traffic congestion and road rage by just observing and recording behaviors at a set of busy traffic lights, without applying any control or altering any variables.

In observational studies, the researcher distinguishes variables and measures their values as they naturally occur. The goal is to capture naturally occurring behaviors, conditions, or events (Ary et al., 2018).

For example, a sociologist might sit in a cafe to observe and record interactions between staff and customers in order to examine social and occupational roles.

There is a significant advantage of observational research in that it provides a high level of ecological validity – the extent to which the data collected reflects real-world situations – as the behaviors and responses are observed in a natural setting without experimenter interference (Holleman et al., 2020)

However, the inability to control various factors that might influence the observations may expose these studies to potential confounding bias, a consideration researchers must take into account (Schober & Vetter, 2020).

Examples

1. Behavior of Animals in the Wild: Zoologists often use observational studies to understand the behaviors and interactions of animals in their natural habitats. For instance, a researcher could document the social structure and mating behaviors of a wolf pack over a period of time.

2. Impact of Office Layout on Productivity: A researcher in organizational psychology might observe how different office layouts affect staff productivity and collaboration. This involves the observation and recording of staff interactions and work output without altering the office setting.

3. Foot Traffic and Retail Sales: A market researcher might conduct an observational study on how foot traffic (the number of people passing by a store) impacts retail sales. This could involve observing and documenting the number of walk-ins, time spent in-store, and purchase behaviors.

Read More: Observational Research Examples

Strengths and Weaknesses

Strengths of Observational Research	Weaknesses of Observational Research
1. Captures data in natural, real-world environments, increasing ecological validity.	1. Cannot establish cause-and-effect relationships due to lack of variable manipulation.
2. Can study phenomena that would be unethical or impractical to manipulate in an experiment.	2. Potential for confounding variables that influence the observed outcomes.
3. Generally less costly and time-consuming than experimental research.	3. Issues of observer bias or subjective interpretation can affect results.

Experimental and Observational Study Similarities and Differences

Experimental and observational research both have their place – one is right for one situation, another for the next.

Experimental research is best employed when the aim of the study is to establish cause-and-effect relationships between variables – that is, when there is a need to determine the impact of specific changes on the outcome (Walker & Myrick, 2016).

One of the standout features of experimental research is the control it gives to the researcher, who dictates how variables should be changed and assigns participants to different conditions (Privitera, 2022). This makes it an excellent choice for medical or pharmaceutical studies, behavioral interventions, and any research where hypotheses concerning influence and change need to be tested.

For example, a company might use experimental research to understand the effects of staff training on job satisfaction and productivity.

Observational research, on the other hand, serves best when it’s vital to capture the phenomena in their natural state, without intervention, or when ethical or practical considerations prevent the researcher from manipulating the variables of interest (Creswell & Poth, 2018).

It is the method of choice when the interest of the research lies in describing what is, rather than altering a situation to see what could be (Atkinson et al., 2021).

This approach might be utilized in studies that aim to describe patterns of social interaction, daily routines, user experiences, and so on. A real-world example of observational research could be a study examining the interactions and learning behaviors of students in a classroom setting.

I’ve demonstrated their similarities and differences a little more in the table below:

Aspect	Experimental Research	Observational Research
Research Objectives	To determine cause-and-effect relationships by manipulating variables.	To explore associations and correlations between variables without any manipulation.
Control	High level of control. The researcher determines and adjusts the conditions and variables.	Low level of control. The researcher observes but does not intervene with the variables or conditions.
Causality	Able to establish causality due to direct manipulation of variables.	Cannot establish causality, only correlations due to lack of variable manipulation.
Generalizability	Sometimes limited due to the controlled and often artificial conditions (lack of ecological validity).	Higher, as observations are typically made in more naturalistic settings.
Ethical Considerations	Some ethical limitations due to the direct manipulation of variables, especially if they could harm the subjects.	Fewer ethical concerns as there’s no manipulation, but privacy and informed consent are important when observing and recording data.
Data Collection	Often uses controlled tests, measurements, and tasks under specified conditions.	Often uses naturalistic observations, surveys, interviews, or existing data sets.
Time and Cost	Can be time-consuming and costly due to the need for strict controls and sometimes large sample sizes.	Generally less time-consuming and costly as data are often collected from real-world settings without strict control.
Suitability	Best for testing hypotheses, particularly those involving cause and effect.	Best for exploring phenomena in real-world contexts, particularly when manipulation is not possible or ethical.
Replicability	High, as conditions are controlled and can be replicated by other researchers.	Low to medium, as conditions are natural and cannot be precisely recreated.
Bias	Risk of demand characteristics or experimenter bias affecting the results.	Risk of observer bias, selection bias, and confounding variables affecting the results.

Conclusion

Experimental and observational research each have their place, depending upon the study. Importantly, when selecting your approach, you need to reflect upon your research goals and objectives, and select from the vast range of research methodologies, which you can read up on in my next article, the 15 types of research designs.

References

Ary, D., Jacobs, L. C., Irvine, C. K. S., & Walker, D. (2018). Introduction to research in education. London: Cengage Learning.

Atkinson, P., Delamont, S., Cernat, A., Sakshaug, J. W., & Williams, R. A. (2021). SAGE research methods foundations. New York: SAGE Publications Ltd.

Creswell, J.W., and Poth, C.N. (2018). Qualitative Inquiry and Research Design: Choosing among Five Approaches. New York: Sage Publications.

Eich, E. (2014). Business Research Methods: A Radically Open Approach. Frontiers Media SA.

Holleman, G. A., Hooge, I. T., Kemner, C., & Hessels, R. S. (2020). The ‘real-world approach’and its problems: A critique of the term ecological validity. Frontiers in Psychology, 11, 721. doi: https://doi.org/10.3389/fpsyg.2020.00721 

Privitera, G. J. (2022). Research methods for the behavioral sciences. Sage Publications.

Sampselle, C. M. (2012). The Science and Art of Nursing Research. South University Online Press.

Schober, P., & Vetter, T. R. (2020). Confounding in observational research. Anesthesia & Analgesia, 130(3), 635.

Tan, W. C. K. (2022). Research methods: A practical guide for students and researchers. World Scientific.

Walker, D., and Myrick, F. (2016). Grounded Theory: An Exploration of Process and Procedure. New York: Qualitative Health Research.