Introduction to Experiments
Welcome to one of the most important chapters in Psychology! In the Research Methods section, we look at how psychologists actually find things out. While there are many ways to study people, the experiment is often called the "gold standard" because it is the only method that can tell us about cause and effect.
In this chapter, we will learn how to build a solid experiment, how to manage variables, and how to design a study that produces results we can trust. Don't worry if some of these terms feel like a new language at first—we'll break them down step-by-step!
1. Variables: The Building Blocks
In any experiment, we are looking at how one thing affects another. These "things" are called variables. There are four main types you need to know for your Edexcel exam:
Independent Variable (IV)
The Independent Variable is the thing the researcher changes or manipulates. It is the "cause."
Example: If you are testing if caffeine helps memory, the IV is whether the person gets caffeine or plain water.
Dependent Variable (DV)
The Dependent Variable is the thing the researcher measures. It "depends" on the IV. It is the "effect."
Example: In the caffeine study, the DV would be the score on a memory test.
Extraneous Variables
These are "nuisance" variables. They are extra things that might affect the DV if we aren't careful, but they can usually be controlled.
Example: The temperature of the room or the time of day during the memory test.
Confounding Variables
These are the "party crashers." A confounding variable is something that did change along with the IV, making it impossible to tell if the IV or the confounding variable caused the result.
Example: If all the people in the caffeine group were naturally gifted at memory tasks and the people in the water group were not, "natural ability" becomes a confounding variable.
Quick Tip: Think of the IV as the Input and the DV as the Data.
Operationalisation
This is a big word for a simple idea: being specific. To "operationalise" a variable means to define exactly how you are going to manipulate or measure it.
Vague: "I will measure memory."
Operationalised: "I will measure the number of words correctly recalled from a list of 20 nouns after 30 seconds."
Key Takeaway
Experiments aim to see how the IV affects the DV while keeping all extraneous variables constant to avoid confounding the results.
2. Hypotheses: Predicting the Future
Before starting an experiment, a researcher must make a clear, testable prediction. This is a hypothesis.
1. Null Hypothesis (\(H_0\)): This predicts that there will be no difference or no effect. Any difference found is just down to chance.
Example: "There will be no difference in the number of words recalled between those who drink caffeine and those who drink water."
2. Alternative Hypothesis (\(H_1\)): This predicts that there will be a difference. It can be written in two ways:
- Directional (One-tailed): You predict which way the results will go. (Use words like "more," "less," "higher," "faster").
Example: "Participants who drink caffeine will recall significantly more words than those who drink water." - Non-directional (Two-tailed): You predict a difference, but you aren't sure which way it will go.
Example: "There will be a significant difference in the number of words recalled between those who drink caffeine and those who drink water."
Did you know? Psychologists usually use a directional hypothesis if previous research suggests which way the results will go. If the area is brand new, they use a non-directional one!
3. Experimental Designs
This is about how you use your participants. How do you split them into groups?
Independent Groups
Participants are split into two (or more) separate groups. One group does Condition A, and the other does Condition B.
+ Pros: No "order effects" (they don't get bored or practiced).
- Cons: Individual differences (e.g., one group might just be naturally smarter).
Repeated Measures
The same participants do both Condition A and Condition B.
+ Pros: No individual differences (you are comparing a person to themselves).
- Cons: Order effects (participants might get better with practice or worse due to boredom/fatigue).
Matched Pairs
Participants are pre-tested on a relevant trait (like IQ). They are paired up, and then one twin-like partner goes to Group A and the other to Group B.
+ Pros: Reduces individual differences without causing order effects.
- Cons: Very time-consuming and difficult to match people perfectly.
Key Takeaway
Choosing a design is a balancing act between avoiding order effects (Repeated Measures) and avoiding participant variables (Independent Groups).
4. Laboratory and Field Experiments
Where you conduct your experiment matters!
Laboratory Experiments
Conducted in a controlled, artificial environment.
Strengths: High control over extraneous variables; easy to replicate.
Weaknesses: Low ecological validity (it's not like real life); high demand characteristics.
Field Experiments
Conducted in the participants' natural environment (e.g., a school or a street).
Strengths: High ecological validity; participants often don't know they are being studied (natural behavior).
Weaknesses: Hard to control extraneous variables; ethical issues (no informed consent).
5. Controlling the Experiment
To make sure our results are valid, we need to use specific control techniques.
Randomisation
Using chance (like flipping a coin or using a random number generator) to decide which participant goes in which group or what order they do tasks in. This reduces researcher bias.
Counterbalancing
This is used in Repeated Measures to fix order effects. Half the group does Condition A then B, while the other half does B then A (the ABBA technique). This way, any boredom or practice effects cancel each other out.
Control Groups
A group that does not receive the IV (e.g., they get a placebo or just sit quietly). We use this as a baseline to compare our experimental group against.
Common Pitfalls to Avoid
- Order Effects: When doing the same thing twice makes you better (practice) or worse (fatigue).
- Demand Characteristics: When participants guess the aim of the study and change their behavior to "help" or "hinder" the researcher.
- Experimenter Effects: When the researcher's body language, tone of voice, or expectations accidentally influence the participants.
Quick Review Box
Check your understanding:
1. What is the variable you measure? (Answer: Dependent Variable)
2. Which design uses the same people in all conditions? (Answer: Repeated Measures)
3. What technique balances out order effects? (Answer: Counterbalancing)
4. A hypothesis that predicts "no difference" is called...? (Answer: Null Hypothesis)