Experimental and Non-Experimental Research, Explained

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Experimental and Non-Experimental Research

Research Methods in Psychology · Chapter 1: Foundations of Psychological ResearchSection 1.5 · lesson 5 of 9411 min · free with a free account

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In this lesson

Choosing the right design for the question at hand.

  • Define experimental and non-experimental designs
  • Name the three features of a true experiment
  • Distinguish correlational, observational and case designs
  • Rule out the rivals before claiming causation

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Transcript

Everything said in the video, section by section (1,383 words). Read along, or search it.

Foundations of Psychological Research

Experimental and Non-Experimental Research

Every research design answers one question before any other. Does the researcher actively change something, or only measure what is already there? That single question splits all psychological research into two families. And it decides what your study will be allowed to conclude. By the end, you will define experimental and non experimental designs. You will name the three features that make an experiment a true experiment. You will tell correlational, observational, case study, and survey designs apart. And you will know exactly why correlation does not imply causation. More usefully, you will know what else you need before you can claim it does. That last skill is one of the most important a researcher ever develops.

The Central Distinction

Manipulate, or Merely Measure

Here is the central distinction, stated plainly. Experimental research manipulates. Non experimental research only observes. In an experiment, the investigator deliberately changes the value of an independent variable. Then observes the effect on a dependent variable, while controlling other influences. In non experimental work, nothing is changed by the researcher. The variables are measured as they already stand. This is not a distinction about topic, or about prestige. It is a distinction about what kind of conclusion the study can support. Which makes it one of the most consequential choices in research design. Get it wrong and you will overclaim, or fail to answer your own question.

Three Defining Features

What Makes an Experiment True

Three features define a true experiment, and all three have to be present. Manipulation of the independent variable. Random assignment of participants to conditions. And control of extraneous variables. Each one closes off a different escape route for a rival explanation. Manipulation establishes that the cause came before the effect. Random assignment rules out pre existing differences between the groups. Control rules out other competing explanations for what you observed. Drop any one of them, and something else could explain your result. That is the whole logic of causal inference, in three moves.

Setting And Sorting

Manipulation and Random Assignment

Take manipulation first. The researcher actively assigns participants to different values of the independent variable. In a study of caffeine and memory, the researcher decides the dose. Zero milligrams, one hundred milligrams, or two hundred milligrams. The participant does not choose. That matters more than it sounds. Manipulation establishes that the independent variable came before the dependent variable in time. That is one essential condition for any causal inference. Random assignment is the second feature, and the most powerful tool in experimental design. It means every participant has an equal probability of landing in any condition. Personality, prior knowledge, mood, motivation. All of it distributed evenly, on average. Without it, any difference between groups could be those pre existing differences talking.

Holding Things Constant

Control, and the Logic of Causation

The third feature is control of extraneous variables. The researcher takes deliberate steps to keep other factors constant. Testing all participants in the same room, at similar times. Identical instructions, and a standardized procedure throughout. Control reduces the chance that an unwanted variable influences the outcome systematically. Now put all three together, and look at what they buy you. Manipulation ensures temporal precedence. Cause before effect. Random assignment rules out pre existing differences between the groups. And control rules out other competing explanations. When all three are in place, only one explanation for a group difference survives. The manipulation itself. That is why only experiments can establish causation.

Three Variants

Laboratory, Field, Quasi

Experiments come in three practical varieties. A laboratory experiment happens in a controlled setting. The researcher can manage almost every aspect of the environment. Maximum control. But there is a cost, and it has a name. Ecological validity is how far findings generalize to real world contexts. A laboratory can sacrifice it. Field experiments apply experimental logic in classrooms, hospitals, workplaces, public streets. Manipulation and random assignment survive. Control over extraneous variables is reduced. That is a deliberate trade, and often a good one. Quasi experiments have manipulation, but no random assignment at all. Comparing students at two schools, or patients at two clinics, can still be valuable. But causal claims are weaker, because pre existing group differences may explain the results.

Where Experiments Stop

Why Non-Experimental Work Is Essential

Many important questions cannot be addressed experimentally, and not for lack of trying. We cannot ethically manipulate childhood trauma. We cannot manipulate biological sex, or country of origin. And we cannot randomly assign people to be depressed, married, or unemployed. Those are not edge cases. They are central variables in psychology. So non experimental research is not a weaker substitute for an experiment. It is indispensable, and it does something an experiment cannot. It observes variables as they naturally occur. The trade is stated up front. You give up strong causal inference. What you get back is access to questions an experiment could never touch.

Measuring Association

Correlational Research

Correlational research measures two or more variables in the same participants. Then it examines whether those variables are associated. The strength and direction of that association get summarized in a correlation coefficient. It runs from minus one, which is a perfect negative relationship. Through zero, which is no relationship at all. To plus one, a perfect positive relationship. Correlation is essential for a great many psychological questions. It is also the design most often over read. On its own it cannot establish causation, however strong the coefficient turns out to be. The size of a correlation tells you how tight the association is, never why it exists.

Observing And Describing

Observation, Case Studies, Surveys

Three more non experimental designs are worth knowing by name. Observational research systematically records behavior in natural settings. Naturalistic observation involves no intervention at all. In participant observation, the researcher takes part in the setting. Structured observation uses predefined coding categories. Observation is particularly valuable in developmental, ethological, and ethnographic research. A case study is an in depth investigation of one individual, group, or event. Patients with rare conditions have profoundly shaped psychology. The amnesia of the patient known as H.M. The frontal injury of Phineas Gage. Case studies offer rich detail, but limited generalizability. Their value lies in generating hypotheses, and illuminating what group studies cannot capture. Survey research collects self report data from large samples, to describe a population.

Three Rivals

Why Correlation Is Not Causation

Now the pitfall this whole section has been building toward. Suppose a study finds that students who exercise regularly report better mental health. The temptation is to conclude that exercise causes the better mental health. Three rival explanations have to be ruled out first. Reverse causation. The dependent variable may be causing the independent variable. Better mental health may simply make people more likely to exercise. The third variable problem. Something unmeasured may be causing both of them. Higher socioeconomic status could produce more exercise and better mental health at once. And coincidence. The relationship may be due to chance in this particular sample. A small or unusual sample can show patterns that vanish when you look again. Notice that none of the three requires the correlation to be false. Each one just offers a different reason why the two things move together.

Side By Side

What Each Family Buys You

Put the two families side by side, and the trade offs become obvious. Manipulation of the independent variable. Yes in experiments, no otherwise. Random assignment. Yes in true experiments, and not possible in non experimental work. Control of extraneous variables. High in experiments, limited elsewhere. Causal inference. Strong in experiments. Weak or impossible without them. Now the two rows that run the other way. Ecological validity is often lower in experiments, and often higher outside them. And for sensitive variables, experiments are often unethical, while observation stays feasible. Typical experimental examples are drug trials and cognitive tasks. Typical non experimental examples are surveys, case studies, and observations. Each design has distinctive strengths. Neither is globally superior to the other.

Choosing Wisely

Match the Design to the Inference

So the question is never which design is better. It is which design the question actually requires. Does this drug reduce anxiety? That calls for a randomized controlled experiment. How do experiences of grief unfold over time? That calls for longitudinal observation. What proportion of citizens hold favorable attitudes toward online education? That calls for a well sampled survey. A skilled researcher matches the design to the inference required. And when causation matters but manipulation is impossible, you build the case another way. Careful longitudinal designs, statistical control of confounds, replication across populations. The strength of a causal claim is proportional to how thoroughly the alternatives were addressed. That is the real skill. Not avoiding causal claims, but earning them.

About Research Methods in Psychology at UPI Study

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Research Methods in Psychology carries a NCCRS credit recommendation. These universities work with NCCRS; some are UPI Study's signed partners. ACE and NCCRS have over 2,100 cooperating colleges that will consider accepting credits; the final decision is with the universities.

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FAQ

Questions students ask us

About Experimental and Non-Experimental Research

What are the three features of a true experiment?
A true experiment needs manipulation of the independent variable, random assignment of participants to conditions, and control of extraneous variables. Manipulation shows the cause came before the effect, random assignment rules out pre-existing differences between groups, and control rules out other competing explanations. If any one is missing, something other than the manipulation could explain the result, which weakens any causal conclusion.
Why does correlation not imply causation?
Two variables can move together without one causing the other. If students who exercise report better mental health, better mental health might lead to more exercise (reverse causation), a third variable such as socioeconomic status might drive both, or the pattern might be chance in that sample. None of these requires the correlation to be false; each offers a different reason the two variables are associated.
What is the difference between a laboratory experiment, a field experiment and a quasi-experiment?
A laboratory experiment runs in a controlled setting with maximum control but possibly lower ecological validity. A field experiment keeps manipulation and random assignment but moves into real settings such as classrooms or hospitals, with less control over extraneous variables. A quasi-experiment involves a manipulation or intervention but no random assignment, such as comparing two schools, so pre-existing group differences weaken its causal claims.
When should researchers use non-experimental research instead of an experiment?
Non-experimental research is used when the variables cannot be manipulated, or should not be, for practical or ethical reasons. Researchers cannot assign people to experience childhood trauma, depression or unemployment, or change their biological sex or country of origin. Correlational, observational, case study and survey designs measure such variables as they naturally occur, trading strong causal inference for access to questions experiments cannot address.

About the Research Methods in Psychology course

How many college credits is Research Methods in Psychology?
Research Methods in Psychology (Psychology 111) carries a NCCRS credit recommendation for 3 semester credits. ACE and NCCRS have over 2,100 cooperating colleges that will consider accepting credits; the final decision is with the universities.
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