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design
— of an experiment details an experimenter’s plan for testing a hypothesis.
The — is the experiment’s structure or floor plan—not the experiment’s specific content
the number of independent variables in the hypothesis
the number of treatment conditions needed to fairly test the hypothesis
whether the same subjects are used in each of the treatment conditions
The experimental design is largely determined by the experimental hypothesis.
A researcher mainly selects an experimental design on the basis of three factors:
between-subjects design
a subject participates in only one condition of the experiment.
different people test each condition, so that each person is only exposed to a single user interface
within-subjects design
the same person tests all the conditions
all participants take part in every condition
random sampling
increases an experiment’s external validity.
10-20
You should have at — subjects in each treatment condition to detect a strong
treatment effect
effect size
is a statistical estimate of the size or magnitude of a treatment effect.
The larger the —, the stronger the relationship between the independent and
dependent variables, and the fewer subjects needed to detect a treatment effect
determines the number of subjects required to detect a treatment effect
power charts
Researchers determine the number of subjects required for an expected effect size using — or programs that incorporate these charts
two group design
involves the creation of two separate groups of subjects.
Two versions of the— are the two independent groups design and two matched groups design
two independent groups design
a design where there is one IV with two levels and subjects are randomly assigned to one of the two conditions.
This design includes the Experimental Group-Control Group design and Two-Experimental Groups design
random assignment
involves assigning subjects to conditions so that each subject has an equal chance of participating in each condition.
We use — to equally distribute subject variables between the treatment groups to prevent them from confounding an experiment
experimental condition
presents a value of the independent variable.
control condition
presents a zero level of the independent variable
experimental group
receives a level of the IV
control group
receives the same procedures, but receives no treatment.
two experimental groups design
In a — we assign subjects to one of two levels of the independent variable.
This design is appropriate if there is one independent variable with two levels and if we can assume that randomization will control extraneous variables.
two matched groups design
In a — we:
1. match participants on a subject variable correlated with the DV, and
2. randomly assign them to one of two treatment conditions
matching
is used to create groups that are equivalent on potentially confounding subject
variables.
Successful — prevents selection threat from undermining internal validity
multiple groups design
is a between-subjects design with more than two levels of an independent variable
multiple independent groups design
In a —, we randomly assign subjects to one of the treatment conditions
The hypothesis, prior research, pilot study results, and practical limits
can all help determine the number of treatments
pilot study
is a trial run of the experiment that uses a few subjects.
can help the experimenter refine the procedure or determine whether the experiment is promising.