1. Writing up results
Week 9.2

2. Cardinal rules Clear Complete
Unambiguous (basically means the same thing as “clear”)

3. Examples

4. t-tests
Choose either one:
Report descriptive statistics;
Plot graph of means and SE or 95% CIs.
Results indicate a significant preference for pecan pie (M = 3.45, SD = 1.11) over cherry pie (M = 3.00, SD = .80), t(15) = 4.00, p = .001.
Ashoka students taking statistics courses in Psychology had higher IQ scores (M = 121, SD = 14.2) than did those taking statistics courses in Statistics (M = 117, SD = 10.3), t(44) = 1.23, p = .05.
Over a two-day period, participants drank significantly fewer drinks in the experimental group (M = 0.667, SD = 1.15) than did those in the wait-list control group (M = 8.00, SD = 2.00), t(43) = 5.51, p < .001.

5. Correlations
Good: Results indicated that the more number of hours participants spent studying, the higher their GPA, r(123) = .61, p = .011.
Acceptable: Hours spent studying and GPA were strongly positively correlated, r(123) = .61, p = .011.
More natural (easier to understand)
Directly explains what the correlation means
More technical (difficult to understand)
It begs the question: What do the correlations mean?

6. Vague reporting
Anxiety scores are correlated with risk taking performance, r(123) = -.61, p = .011.
There is a gender difference on risk taking, t(43) = 5.51, p < .001.
Does a high score in risk taking performance indicate more or less risky behavior?
Which gender is higher?
Does a higher score in risk taking performance indicate more or less risky behavior?

7. Recall: ANOVAs Report: If interaction is significant:
Interactions
Main effects
If interaction is significant:
If 2 x 2 design, report all four simple effects
More complicated than 2 x 2, select conditions where the comparisons are meaningful to report
Misconception alert: Do not think that “meaningful results” only refer to statistically significant results; null results can also be meaningful! For example, the lack of a difference between cultures may indicate that the phenomenon is universal.

8. Reporting ANOVA results: My style
Starting:
“A [design, factor label, levels, type of ANOVA] on [DV] revealed [Main Effect 1?], [Main Effect 2?].”
If interaction is present:
“More importantly, these were qualified by an interaction between [IV1] and [IV2], [results of interaction].”
If interaction is not present:
“There was no interaction between [IV1] and [IV2], [results of interaction].”

9. Reporting ANOVA results: My style
Reporting simple effects:
“See Figure 1. Simple effects revealed that in [Condition A1], [results of B1 vs. B2]. For [Condition A2], [results of B1 vs. B2]. In addition, in [Condition B1], [results for A1 vs. A2], and in [Condition B2], [results for A1 vs. A2].”
Make use of conjunctions to achieve a more conversational description
“however”, “in contrast”, “whereas”, “especially”, “ also”, “but not”, etc.

10. Example
A 2 (Music Played: Hindustani vs. Classical) x 2 (Music Preference: Hindustani classical vs. Western classical) fully between-subjects ANOVA on memory revealed no main effect of Music Played, F(1, 38) = 0.44, p > .99, and no main effect of Music Preference, F(1, 38) = 0.44, p > .99. There was, however, a significant interaction between the two factors, F(1, 38) = 3.22, p = See Figure 1. Simple effects analyses indicated that when people heard Western classical, they remembered more words only if they reported liking Western classical music over Hindustani classical music, t(18) = 2.10, p = .02. The converse was true: When people heard Hindustani classical, they remembered more words only if they reported liking Hindustani classical music over Western classical music, t(18) = 2.10, p = .02. In addition, for those who preferred Western classical, they remembered more words when Western classical music was played, t(18) = 2.10, p = .02; for those who preferred Hindustani classical, they remembered more words when Hindustani music was played, t(18) = 2.10, p = .02.
Why is this good to have?
If you don’t write the last two simple effects, readers could reconstruct your graph this way, couldn’t they?
Your readers should be able to reconstruct a graph based purely on your description.
Lesson: Be clear, complete, and _____

11. Advanced tips Try to weave your results into a story (prose)
Don’t be too mechanical – it shows that you actually don’t understand your results
But don’t be too creative such that your reporting becomes too vague
From your results, one should be able to reconstruct a graph without any information about the means and error bars.
Read empirical papers slowly. See how other researchers write.