Podcast
Questions and Answers
What is the primary approach for including multiple independent variables in an experiment?
What is the primary approach for including multiple independent variables in an experiment?
- Quasi-experimental design
- Factorial design (correct)
- Causal-comparative design
- Single-factor design
In a 2 × 2 factorial design, what does each number represent?
In a 2 × 2 factorial design, what does each number represent?
- The number of variables with levels
- The number of participants in each condition
- The total number of conditions in the experiment
- The number of levels for each independent variable (correct)
How many conditions are there in a 3 × 2 factorial design?
How many conditions are there in a 3 × 2 factorial design?
- 9
- 8
- 6 (correct)
- 5
Which of the following factorial designs has three independent variables?
Which of the following factorial designs has three independent variables?
What is the total number of conditions in a 4 × 5 factorial design?
What is the total number of conditions in a 4 × 5 factorial design?
How many levels does the independent variable in a 3 × 3 factorial design have?
How many levels does the independent variable in a 3 × 3 factorial design have?
In a simple between-subjects design, how are participants tested?
In a simple between-subjects design, how are participants tested?
What can be inferred from the notation 2 × 3 × 2 in a factorial design?
What can be inferred from the notation 2 × 3 × 2 in a factorial design?
What is the correct interpretation of a factorial design table?
What is the correct interpretation of a factorial design table?
If an independent variable has three levels and another has two levels, which design notation represents this?
If an independent variable has three levels and another has two levels, which design notation represents this?
What is a primary characteristic of a between-subjects factorial design?
What is a primary characteristic of a between-subjects factorial design?
Which of the following is a key advantage of using a within-subjects design?
Which of the following is a key advantage of using a within-subjects design?
In a mixed factorial design, how are the independent variables manipulated?
In a mixed factorial design, how are the independent variables manipulated?
What is a potential downside of the between-subjects design?
What is a potential downside of the between-subjects design?
Which situation exemplifies a within-subjects design?
Which situation exemplifies a within-subjects design?
What method is typically used for assigning participants in factorial designs?
What method is typically used for assigning participants in factorial designs?
Which of the following describes an example of a between-subjects factor?
Which of the following describes an example of a between-subjects factor?
What is one major advantage of the between-subjects factorial design?
What is one major advantage of the between-subjects factorial design?
Which of the following is a typical requirement for within-subjects designs?
Which of the following is a typical requirement for within-subjects designs?
What is a common advantage of using factorial designs in research?
What is a common advantage of using factorial designs in research?
Flashcards
Factorial Design
Factorial Design
An experimental design where multiple independent variables (factors) combine to create all possible combinations as experiment conditions.
2 x 2 Factorial Design
2 x 2 Factorial Design
An experiment that tests two independent variables each with two levels.
3 x 2 Factorial Design
3 x 2 Factorial Design
Combines one independent variable with 3 levels, and another independent variable with 2 levels, creating 6 conditions.
Number of Independent Variables
Number of Independent Variables
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Number of Levels
Number of Levels
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Conditions in an experiment
Conditions in an experiment
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Between-Subjects Design
Between-Subjects Design
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Within-Subjects Design
Within-Subjects Design
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Independent Variable
Independent Variable
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Levels of an independent variable
Levels of an independent variable
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Between-subjects factorial design
Between-subjects factorial design
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Within-subjects factorial design
Within-subjects factorial design
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Mixed factorial design
Mixed factorial design
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Factorial experiment
Factorial experiment
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Order effects
Order effects
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Counterbalancing
Counterbalancing
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Study Notes
Factorial Designs
- Factorial designs are the most common way to include multiple independent variables (factors) in experiments.
- Each level of one independent variable is paired with every level of the other independent variables.
- This creates all possible combinations, each becoming a unique experimental condition.
Example: 2 x 2 Factorial Design
- Example: Investigating cell phone use (yes/no) and time of day (day/night) impact on driving.
- This creates four conditions: using phone during day, not using phone during day, using phone at night, not using phone at night.
Notation and Conditions
- Notation (e.g., 2 x 2, 3 x 2) shows the number of independent variables and their levels.
- Each number corresponds to a factor (variable).
- The value of each number indicates the number of levels for that factor.
- Number of conditions = product of the numbers of levels.
Independent Variables and Levels
- A 2 x 2 design has two independent variables, each with two levels.
- A 3 x 3 design has two independent variables, each with three levels.
- A 2 x 2 x 2 design has three independent variables, each with two levels.
Between-Subjects vs. Within-Subjects
- Between-subjects: Each participant is tested in only one condition.
- Within-subjects: Each participant is tested in all conditions.
- Factorial experiments require a decision about each independent variable (between or within design).
Mixed Factorial Designs
- In a mixed factorial design, some independent variables are manipulated between subjects, and others within subjects.
- Example: cell phone use (within subjects) and time of day (between subjects).
- Each participant is tested in a subset of conditions.
Random Assignment
- Regardless of the design, participants are typically assigned to conditions or orders of conditions randomly.
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