Introduction (1-2 pages) The intro should contain three to five paragraphs

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Introduction (1-2 pages)

The intro should contain three to five paragraphs. In the first paragraph, explain the broad question using a real-world example, and tell the readers the purpose of your study. In the middle paragraph(s), introduce the relevant research you’ve found and explain its connection to the study you’re presenting now. In the final paragraph, explain the specific question, the hypotheses (alternatives), and the logic behind YOUR study. Then briefly explain what participants will do.

Cite at least three papers (the Yin 1969 paper and at least two others of your choosing that are relevant to our study). Also, be sure to explain and justify three hypotheses (remember that every 2x2 experiment will involve three possible hypotheses):

• Whether there will be a main effect of type of object type.
  • Specify: The error rates will be significantly higher/lower for the house images than those for the face images, or not different at all
• Whether there will be a main effect of orientation.
  • Specify: The error rates will be significantly higher/lower for the inverted images than those for the upright images, or not different at all
• Whether there will be an interaction effect between type of task and orientation
  • Specify:  There will be a greater/smaller difference in error rates between upright and inverted images for faces than for houses, or there will be no difference at all

 

Methods (1-2 pages)

The methods section should be a complete recipe that anyone could follow to replicate your experiment. At the same time, you should be as brief as possible.

Participants?

• How many people? where did they come from?

Materials?

• How many images total, and how many images per condition (face upright, face inverted, house upright, house inverted)?

Procedure?

• What was the design—IVs, DVs, within/between/mixed?
• How many phases? in the study? Describe each phase in detail.  
  • First the study phase was conducted, then the test phase was conducted. Error rates were recorded during the test phase. (Don’t use this exact wording).

 

Results

The results section is used to report the patterns in the data, and the statistical support for those patterns.

• e.g., “Mean error rates from each condition were submitted to a 2 (object type: face vs. house) x 2 (orientation: upright vs. inverted) within-subjects ANOVA.”
  • Tell the reader where they can see the data.
    • e.g., “The results of experiment 1 are presented in table 1, or in figure 1?”
      • Make a table or figure to display the data in your paper
• Describe the pattern of each main effect and the interaction effect (depending on whether each one is statistically significant) and back it up with statistics.
  • It’s not enough to simply say there was a main effect (remember that ANOVAs alone tell us that there is a difference, but not necessarily what the difference looks like). It’s up to you to point out the specific comparisons (running post-hoc tests if necessary) and tell the reader how the condition means compare to (and, if applicable, interact with) each other.

Example of reporting main/interaction effects for an ANOVA:

• “There was a main effect of type of task (F(df, df) = X.XX, p = X.XX) such that the error rates were significantly higher/lower for the house images (M= ) than for the face images (M=  ).”
• “There was a main effect of orientation (F(df, df) = X.XX, p = X.XX) such that the error rates were significantly higher/lower for the inverted images (M= ) than for the upright images (M=  ).”
• “There was an interaction effect between type of task and orientation (F(df, df) = X.XX, p = X.XX) such that there was a greater/smaller difference in error rates between upright and inverted images for the face images condition than there was for house images.”
• If any of these effects is not significant, simply say there was no main/interaction effect and report the p value.
   

 

Discussion

Discuss each result or lack thereof (the main effect for orientation, the main effect for type of task and the interaction effect between orientation and the type of task). Connect it to the ideas you presented in the discussion. What does it mean for your hypotheses? What did we learn?

Then, branching out, how do these results compare to what other researchers, like Yin, have found? Are they the same? Are they different? Why do you think they turned to be the same/different? The answer could be theoretical, methodological, or both. Also, are there alternative ways of interpreting the results that we haven’t thought about in class?

What limitations does our study have? What ideas and suggestions do you have for future research on this topic?
References

Add the three (or more) references that you cited in the manuscript.

Face Inversion Experiment Fact Sheet

 

Number of subjects: 46 participants

• • # of people that participated in this experiment
    • In most data formats, each row is a participant, so the data will have 47 rows (46 participants + the column headers)
  • In the Jamovi output, your descriptive statistics should have the “N” (number of subjects)
• Study phase (or inspection phase)

96 images total

• • • 50% were faces/houses
    • 50% were upright/inverted
    • Note: the images’ orientations were all the same in the study phase as in the test phase (e.g., if an image appeared upright in the study phase, it also appeared upright in the test phase)
  • Each image was presented for 2 seconds
• Test phase
  • Participants were shown two images at the same time
    • One image was old (previously presented during the study phase)
    • One image was new
  • Participants required to click on the “OLD” image using the mouse

 

• Experimental design:
  • Independent variables (or factors):
    • Two: Object type and Orientation
    • Number of levels per factor? Two
      • Object type: Faces, Houses
      • Orientation: Upright, Inverted
    • Between-subjects, within-subjects, or mixed-factorial? Within
  • Dependent variable: Error rate, or percentage of incorrect responses—that is, the percentage of trials in which new (not previously seen) pictures were wrongly identified as old (previously seen)