Variables Refresher

• Independent Variables (IVs)
  • Things you manipulate or measure
  • Categorical: Groups (e.g., high/low, young/old)
• Dependent Variables (DVs)
  • Things that you measure
  • Continuous/Ordinal: Responses from participants

Understanding YOUR Design

• Your design uses 2 IVs with 2 levels each
• Identify your specific variables and levels
• Focus solely on your own design in your write-up

Types of 2x2 ANOVA Designs

1. Between-subjects design
   • Different participants in each condition
   • Both IVs are between-subjects factors
   • 4 ‘groups’ of participants

Types of 2x2 ANOVA Designs (cont.)

2. Repeated measures design
   • All participants in all conditions
   • Both IVs are within-subjects factors
   • 1 ‘group’ of participants

Types of 2x2 ANOVA Designs (cont.)

3. Mixed design
   • One IV is repeated measures (within-subjects)
   • One IV is between-subjects
   • 2 ‘groups’ of participants

Final Data Collection Steps

• Data collection is complete
• Ensure your dataset is clean and analysis should be on the go!
• Document any preprocessing steps in your methods section

What to Expect in Analysis

• 2x2 ANOVA is the only required inferential analysis
• Even if assumptions are violated, still conduct and report the ANOVA
• Include post-hoc tests for significant interactions
• Report means, standard deviations, and effect sizes

IMRAD+ Format

1. Title: Concise, descriptive, reflects your variables
2. Abstract: Brief summary (150-250 words)
3. Introduction: Literature review → specific hypotheses
4. Methods: Design, Participants, Materials, Procedure

IMRAD+ Format (cont.)

5. Results: Statistics, visualizations, patterns
6. Discussion: Interpretation, limitations, implications
7. References: APA 7 format
8. Open Data & Materials: Replication package

IMRAD+ Format (cont.)

9. Reflective Account: Min 200 words - Engagement with the process

Introduction

• Move from general topics to specific hypotheses
• Establish clear rationale for your study
• Present relevant literature concisely and consider both IVs, DV and methods
• End with explicit hypotheses

Methods

• Design: Your specific 2x2 design with variables/levels/type
• Participants: Demographics, sampling approach
• Materials: Detailed description of all measures and Stuff used
• Procedure: Clear overview of experimental protocol (step-by-step)

Results

• Descriptive statistics: Means, standard deviations, patterns
• Inferential statistics: Main effects and interactions from ANOVA
• Include visualizations (graphs, tables)
• Focus on relevant outputs (p-values, effect sizes)

FAQ - SPSS output

Discussion

• Interpret whether hypotheses were supported
• Connect findings to existing literature
• Discuss limitations honestly
• Suggest meaningful future directions

Open Data

• Must be useful for re-analysis
• Can include:
  • Raw data from platforms (e.g., Qualtrics)
  • Processed data with corrections
  • Analysis-ready datasets

Open Materials

• A package of all study materials
• Should allow for immediate reproduction
• Include consent forms, questionnaires, stimuli
• Provide clear documentation

Reflective Account

• At least 200 words
• Demonstrate reflective practice and metacognition
• Avoid negativity; focus on learning
• Consider your personal growth as a researcher

Product Is Not the Outcome

Think of your research project like a cooking apprenticeship:

• A chef doesn’t just learn by creating perfect dishes
• They learn through challenges: ingredient interactions, timing issues, technique refinement
• Even when a dish doesn’t turn out as expected, the knowledge gained is invaluable

Product Is Not the Outcome (cont.)

Similarly, your research project develops crucial skills:

• Experimental design
• Data collection and analysis for real
• Scientific writing and critical thinking

The true measure of success isn’t your p-value, but the research toolkit you’re developing.

Presentation Matters

• Quality of presentation impacts grading
• Use visuals to enhance understanding
• Ensure consistent formatting, no weird fonts or formats
• Proofread carefully and edit viciously

Avoid Data Paralysis

• The analysis is maybe not the funnest part - I hear you!
• But it is only a small part of the exercise
• You can show your lab-tutor on screen or get support in labs
• Don’t over-egg it, and don’t put it off

Data Analysis Focus

• Report only relevant statistical outputs
• Interpret what your results actually mean
• Link analysis back to your hypotheses
• Be precise in your reporting - don’t shove in everything in case it’s useful

Completeness Is Critical

• Use the rubric and marking guidelines
• Ensure no required sections are missing
• Incomplete submissions are capped at 2:1
• Double-check everything before submission

Feedback Opportunities

• Lab tutors can review all aspects of your work
• Not showing work means missing valuable feedback
• Don’t wait until after submission to seek help
• Use lab sessions to get input on your progress

General Questions

Word count worries

Common Data Mistakes to Avoid

Common Writing Mistakes to Avoid

Common Formatting Mistakes to Avoid

Tips for Success

Addressing Concerns

Extensions and Communication

Additional Resources

• Writing Guide: Detailed advice on each section
• Statistical Resources: Templates for ANOVA analysis
• Rubric: Essential for checking completeness