Podcast
Questions and Answers
What percentage of the final exam is derived from material covered after the midterm?
What percentage of the final exam is derived from material covered after the midterm?
How many multiple choice questions are included in the final exam?
How many multiple choice questions are included in the final exam?
Which of the following types of material is tested the least on the final exam?
Which of the following types of material is tested the least on the final exam?
Which of the following is NOT considered a type of hypothesis or design covered in the course?
Which of the following is NOT considered a type of hypothesis or design covered in the course?
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Which statistical test is used to analyze factorial designs?
Which statistical test is used to analyze factorial designs?
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What does the F-value represent in the context of ANOVA?
What does the F-value represent in the context of ANOVA?
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What is indicated if a difference between means is treated as significant?
What is indicated if a difference between means is treated as significant?
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Which of the following patterns indicates a main effect of factor A but no main effect of factor B?
Which of the following patterns indicates a main effect of factor A but no main effect of factor B?
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When interpreting factorial designs, which means are compared to assess success and failure?
When interpreting factorial designs, which means are compared to assess success and failure?
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What is a primary use of combining true independent variables (IVs) and participant variables (PVs)?
What is a primary use of combining true independent variables (IVs) and participant variables (PVs)?
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What does it mean if the participant variable is described as a 'moderator' in the context of an interaction?
What does it mean if the participant variable is described as a 'moderator' in the context of an interaction?
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Which of the following statements is true regarding causal conclusions in studies involving participant variables?
Which of the following statements is true regarding causal conclusions in studies involving participant variables?
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What is the primary role of a moderator in an experimental context?
What is the primary role of a moderator in an experimental context?
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In the factorial design context, which method involves measuring the same participants across different conditions?
In the factorial design context, which method involves measuring the same participants across different conditions?
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In a 2 x 2 factorial design, how many distinct combinations of the independent variables (IVs) are tested?
In a 2 x 2 factorial design, how many distinct combinations of the independent variables (IVs) are tested?
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Which is a caution to consider when interpreting results that involve participant variables?
Which is a caution to consider when interpreting results that involve participant variables?
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How many conditions are present in a 2 x 3 factorial design?
How many conditions are present in a 2 x 3 factorial design?
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What factorial notation corresponds to a design with 2 independent variables, both having 3 levels?
What factorial notation corresponds to a design with 2 independent variables, both having 3 levels?
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What is the total number of cells in a 2 x 2 x 2 factorial design?
What is the total number of cells in a 2 x 2 x 2 factorial design?
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Which of the following describes how to represent the lowest number of conditions possible in factorial notation?
Which of the following describes how to represent the lowest number of conditions possible in factorial notation?
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In a 3 x 4 factorial design, how many levels does each independent variable have?
In a 3 x 4 factorial design, how many levels does each independent variable have?
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In a factorial design with three factors that each have two levels, what would be its notation?
In a factorial design with three factors that each have two levels, what would be its notation?
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What does an interaction effect indicate in the context of Factor A and Factor B?
What does an interaction effect indicate in the context of Factor A and Factor B?
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In the interaction hypothesis example involving anxiety and performance, how does task difficulty influence anxiety levels?
In the interaction hypothesis example involving anxiety and performance, how does task difficulty influence anxiety levels?
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What is one key characteristic of a main effect in an interaction analysis?
What is one key characteristic of a main effect in an interaction analysis?
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Based on the provided data example, what can be concluded about the effect of task importance on performance levels?
Based on the provided data example, what can be concluded about the effect of task importance on performance levels?
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How do parents' reactions influence the relationship between violent media and children's aggression?
How do parents' reactions influence the relationship between violent media and children's aggression?
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What was indicated by the significant main effect of performance level?
What was indicated by the significant main effect of performance level?
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What conclusion can be drawn regarding task importance based on the main effect analysis?
What conclusion can be drawn regarding task importance based on the main effect analysis?
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How did the interaction between performance level and task importance manifest for important tasks?
How did the interaction between performance level and task importance manifest for important tasks?
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Which statement accurately describes the overall interaction effect between performance level and task importance?
Which statement accurately describes the overall interaction effect between performance level and task importance?
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What does a significant interaction effect imply in the context of the study?
What does a significant interaction effect imply in the context of the study?
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According to the findings, what was the result for self-esteem levels on unimportant tasks?
According to the findings, what was the result for self-esteem levels on unimportant tasks?
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Which of the following statements about the significance of interactions in this study is true?
Which of the following statements about the significance of interactions in this study is true?
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What statistical result indicates a significant main effect of performance level?
What statistical result indicates a significant main effect of performance level?
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Flashcards
Final Exam Date
Final Exam Date
Saturday, December 7, 8:30-10:30 AM
Exam Duration
Exam Duration
2 hours
Exam Content Emphasis
Exam Content Emphasis
Lectures weeks 9-14 (60%) and material covered heavily in class (80%).
Exam Question Types
Exam Question Types
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Exam Material
Exam Material
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Factorial Designs
Factorial Designs
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Main Effect
Main Effect
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Interaction Effect
Interaction Effect
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Analysis of Variance (ANOVA)
Analysis of Variance (ANOVA)
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Significance Level
Significance Level
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Moderator Variable
Moderator Variable
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2 x 2 Factorial Design
2 x 2 Factorial Design
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Levels of a Factor
Levels of a Factor
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Conditions in a Factorial Design
Conditions in a Factorial Design
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2 x 3 Factorial
2 x 3 Factorial
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Factorial Notation
Factorial Notation
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Cells in a Factorial Design
Cells in a Factorial Design
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How can you tell if there's an interaction effect?
How can you tell if there's an interaction effect?
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Example: Task Difficulty and Anxiety
Example: Task Difficulty and Anxiety
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Example: Violent Media and Aggression
Example: Violent Media and Aggression
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Significant Interaction
Significant Interaction
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Qualify the Main Effect
Qualify the Main Effect
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Importance of Interaction
Importance of Interaction
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Describe an Interaction
Describe an Interaction
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Generic Interaction Template
Generic Interaction Template
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Interaction Example
Interaction Example
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IV x PV design
IV x PV design
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Moderator
Moderator
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Independent Groups Design
Independent Groups Design
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Within Groups Design
Within Groups Design
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Mixed Design
Mixed Design
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Study Notes
Final Exam Information
- The final exam is on Saturday, December 7th, from 8:30 AM to 10:30 AM.
- Multiple locations are available in BA. Refer to the Exam Information document for specific locations.
- The exam is 2 hours long.
- The exam is worth 100 points.
- 80 points are multiple choice.
- 20 points are short answer (10 questions, 2 points each).
- The format of the short answer questions is similar to the midterm format.
- No aids are permitted, including calculators.
- Material covered includes lecture weeks 1–14, chapters 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13 (pages 401–418), chapter 14, and the statistics module (pages 467–479). Chapter 3 from the price text is also included (PDF version in the course information folder).
- The exam emphasizes material covered after the midterm, which accounts for approximately 60% of the exam. This corresponds to lecture weeks 9-14 and text chapters 9-14.
- Approximately 80% of the lecture and text shared material will be covered on the exam.
- Approximately 10% of the lecture-only material will be tested.
- Approximately 10% of the textbook-only material will be tested (by multiple-choice questions).
- Approximately 2% of the lab-only material will be tested (by multiple-choice questions).
Week 1 Outline
- Simple vs. more complex hypotheses and designs
- Testing interaction hypotheses
- Factorial designs
- Describing features of factorial designs (Terminology: variables, levels, conditions) Independent-groups, within-groups, mixed
- Manipulated IVs vs. Participant Variables
- Interpreting results of a 2 x 2 factorial design
- Example experiment
- Types of effects: main effects, interaction
- A note on statistical significance
- The possible patterns of results
- Identifying effects in tables and graphs
- Extensions and variations
- Increasing the number of levels of an IV
- Increasing the number of IVs
Week 1 Outline (Continued)
- More on interpreting main effects and interactions
- Follow-up tests
- Interaction effects are more important
- Describing in words
- Combining IVs and PVs
- Uses of IV x PV designs
- Cautions in interpreting results
- Assignment to conditions in factorial design
- Independent-groups designs (between)
- Within-groups designs (within)
- Mixed designs (between-within)
- Advantages and uses of factorial designs
- Advantages of factorial designs compared to one-way designs
- Uses of factorial designs
- Identifying factorial designs in your reading
Simple Causal Hypotheses
- State the effect that one IV will have on a dependent variable (DV).
- Tested in "one-way" designs with one IV.
- Conclusions are "general" or "unqualified."
- Prompts research to specify conditions under which the effect disappears or grows stronger.
- Boundary conditions
More Complex Causal Hypotheses
- State how two (or more) IVs affect a DV.
- Called "interaction hypotheses" because they specify how independent variables "interact" to influence a dependent variable.
- Can lead to more "qualified" conclusions about behavior
Interaction Hypothesis: Example (Examples of different hypothesis tests)
- The effect that X has on Y depends on Z.
- The effect that anxiety has on performance depends on task difficulty.
- When tasks are easy, increases in anxiety produce increases in performance.
- When tasks are difficult, increases in anxiety produce decreases in performance.
- The effect that violent media has on children's aggression depends on their parents' reactions.
- When parents react favorably, more violence watched, the more aggressive the child will be.
- When parents react unfavorably, more violence watched, the less aggressive the child will be.
Interaction Hypotheses: Testing for Moderators
- A moderator is a variable that changes the strength of association between two other variables.
- In experiments, a moderator is an independent variable that changes the strength of the effect another IV has on the DV.
- The effect that anxiety has on performance is moderated by task difficulty.
- The effect that media violence has on aggression is moderated by the parents' reactions.
Describing Factorial Designs
- A research design that tests the effect of two or more factors (IVs) simultaneously.
- Each factor is "crossed" with each other factor, creating all possible combination.
- The number of conditions (or "cells") is the product of the number of levels of each factor.
2 x 2 Factorial Design
- See tables in document.
2 x 4 Factorial Design
- See table in document.
2 x 3 Design, example #1 and #2
- See tables in document.
3 x 3 Design Example
- See table in document.
2 x 4 Design Example
- See table in document.
2 x 2 x 2 Design Example
- See table in document.
Interpreting Higher Order Factorial Designs
- With three factors, there are three main effects (performance level, task importance, presence of others), three two-way interactions (performance level x task importance, performance level x presence of others, task importance x others), and one three-way interaction (performance level x task importance x others).
Examining 2-way Interactions in a Higher Order Design
- Examine each 2-way interaction by ignoring or "collapsing across" the remaining factors.
Examining the 3-way Interaction in a 3-way Design
- A 3-way design can provide information about the combined effects of all three factors.
- There will be a 3-way interaction if a two-way interaction between two factors differs depending on the other remaining factor.
- Ask: Does a two-way interaction differ across the levels of the remaining factor?
- Examine the two-way interaction pattern at each level of the remaining factor.
Follow-Up Tests
- If the IV has only two levels, no further tests are needed.
- If the IV has more than two levels, further tests are needed to interpret the findings.
- Called "post hoc tests" or "multiple comparisons"
- Want to determine precisely which of the marginal means differ significantly from each other
Post Hoc Tests
- See tables in document.
Describing Main Effects and Interactions in Words
- Main effects (without an interaction)
- Main effects (with an interaction)
- Interaction effects
Example: One Main Effect without an Interaction
- There was no significant main effect of task importance.
- There was a significant main effect of performance level
- The interaction between performance level and task importance was not significant.
Example: One Main Effect with an Interaction
- There was no significant main effect of task importance
- There was a significant main effect of performance level
- The effect of performance level was qualified by a significant interaction between performance level and task importance.
Interactions are More Important than Main Effects
- When a study shows both a main effect and an interaction, the interaction is almost always more important.
- This interaction qualifies the main effect.
- There may be real differences in marginal means, but the more interesting part is the interaction.
Describing an Interaction: Generic Templates
- The interaction between factor A and factor B indicates the effect of factor A differs depending on the levels of factor B.
- For example, when first level B is present, increases in factor A result in higher scores in DV, and in the contrast, when second level B is present, increases in factor A result in lower scores in DV.
Pattern #6b – Alternate Example
- See table in document.
Description of Interactions in Words: Textbook Examples
- Describe the interactions.
Recall: Interaction Hypothesis Example
- The effect of X on Y depends on Z.
- The effect of anxiety on performance depends on task difficulty.
- When tasks are easy, increases in anxiety increase performance.
- When tasks are difficult, increases in anxiety decrease performance.
- The effect that violent media has on children's aggression depends on their parents' reactions.
- When parents react favorably, more violence watched, the more aggressive the child will be.
- When parents react unfavorably, more violence watched, the less aggressive the child will be.
Combining IVs and PVs
- Sometimes called IV x PV designs
- Use to test the generality of an IV's effect on the DV for different kinds of people.
- Use to test the association between a participant variable (PV) and the DV in different situations
- Cautions in interpreting results: cannot draw causal conclusions for effects involving the participant variable; Participant variable might moderate the effect of the IV; participant variable can be called a moderator if there is an interaction. Given examples with Depression diagnosis and Experience with Task (2 variables to the participant).
Assignment to Conditions and Orders
- Independent Groups (Between-subjects)
- Within-Groups (Repeated Measures)
- Mixed-factorial design
Independent-Groups Design
- Random assignment of participants to conditions. For example, 2 x 3 design will have 6 different conditions.
Within-Groups Design
- Each participant is in each factorial condition. For example, conditions were arranged as a sequence or order, that is measured or assessed across time.
Mixed-Factorial Designs (Between-Within)
- A study with at least one independent-groups and one within-groups factor.
Tests of Simple Effects
- Simple effects of A at B1
- Simple effects of A at B2
- Simple effect of B at A1
- Simple effect of B at A2
Identifying Factorial Designs in Your Readings
- The method section will describe the design of the study (including factorial notation).
- The results section will examine whether main effects and interactions were significant.
- Look for “it depends” or “only when” to highlight an interaction.
- Look for participant variables (age, gender, ethnicity).
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Description
Prepare for your Statistics final exam with this comprehensive quiz that covers key concepts from factorial designs to ANOVA. Test your knowledge on the material, multiple choice questions, and the significance of various hypothesis types. This quiz will help you assess your readiness for the exam and deepen your understanding of the course content.
