What is independent group design?
Independent measures design, also known as between-groups, is an experimental design where different participants are used in each condition of the independent variable. This means that each condition of the experiment includes a different group of participants.
What is an example of independent groups design?
An independent measures design is a research method in which multiple experimental groups are used and participants are only in one group. Each participant is only in one condition of the independent variable during the experiment. An example would be a drug trial for a new pharmaceutical.
What are independent groups examples?
Independent samples Independent groups are more common in hypothesis testing. For example, the following experiments use independent samples: A medication trial has a control group and a treatment group that contain different subjects. A study assesses the strength of a part made from different alloys.
What is an advantage of using independent groups design?
Independent groups design
| Independent groups design | |
| Advantages No order effects Lower risk of demand characteristics Same tests/materials can be used | Disadvantages Participant variables More participants required than with repeated measures design |
| Evaluation |
When Should independent groups design be used?
INDEPENDENT GROUPS DESIGN One group becomes the experimental condition and the other group becomes the control condition. Sometimes a researcher has to use independent groups design. For example, if the IV is naturally-occurring, like “gender”, and it’s just not possible to assign someone to both conditions.
What is a strength of independent groups design?
A strength of the independent measures design is that because participants only take part in one condition participants are less likely to become border or practiced and therefore the experiment is more likely to measure natural real-life behaviour.
What are the types of experiments?
There are three types of experiments you need to know:
- Lab Experiment. Lab Experiment. A laboratory experiment is an experiment conducted under highly controlled conditions (not necessarily a laboratory), where accurate measurements are possible.
- Field Experiment. Field Experiment.
- Natural Experiment. Natural Experiment.
What is meant by independent groups?
The independent groups design is an experimental design whereby two groups are exposed to different experimental conditions. Usually half of the participants are assigned to the experimental group where they are exposed to a condition where the independent variable is manipulated.
How do you identify a quasi experimental design?
Like a true experiment, a quasi-experimental design aims to establish a cause-and-effect relationship between an independent and dependent variable. However, unlike a true experiment, a quasi-experiment does not rely on random assignment. Instead, subjects are assigned to groups based on non-random criteria.
Which is an example of an independent group design?
What this means is that each participant in each group in an experiment only experiences one condition of the independent variable. In our alcohol reaction time example (click repeated measures design) this would see one group undergoing the control condition and getting no alcohol and doing…
What does between groups mean in experimental design?
This type of design is also known as between groups. Different participants are used in each condition of the independent variable. This means that each condition of the experiment includes a different group of participants.
What is the definition of independent measures design?
Independent Measures Design. An independent measures design is a research method in which multiple experimental groups are used and participants are only in one group. Each participant is only in one condition of the independent variable during the experiment.
How are independent groups used in an experiment?
Independent groups design is an experimental design where different participants are used in each condition of the experiment. Random allocation should be used to decide to which condition each participant should be allocated, as this ensures that each participant has an equal chance of being assigned to one group or another. Learn more ›.
