Writing up results This tutorial focuses on writing your results section. Click the next button in the bottom right hand corner to begin. Next QUIT.

Presentation on theme: "Writing up results This tutorial focuses on writing your results section. Click the next button in the bottom right hand corner to begin. Next QUIT."— Presentation transcript:

Writing up results This tutorial focuses on writing your results section. Click the next button in the bottom right hand corner to begin. Next QUIT

Logic of Writing up Research Results: Overview In writing the results section, try to make it as clear and as understandable as possible, go from the simple findings to the more complex, emphasize results that pertain to the hypothesis more than results that are irrelevant to the hypothesis, and emphasize significant effects more than nonsignificant effects. Next

Putting the Information in Order: Overview Usually, information in the results section goes in the following order: 1. A description of how a participant's behavior was turned into a score (unless this is not necessary) 2. Results supporting the measure's validity 3. Results supporting the validity of the manipulation 4. Results relating to the hypothesis 5. Other statistically significant results

Organizing Your Results Section: Step 1 1.Unless it is obvious what your scores represent, tell the reader what the scores you are going to analyze represent. That is, what does a participant do to get a certain score? Example

Organizing Your Results Section: Step 2 2. Tell the reader what analysis you are doing and tell the reader what question that analysis will let you answer. Examples

Organizing Your Results Section: Step 3 3. Tell the reader whether the analysis supports your prediction, then back up this claim with both the results of the statistical test and descriptive statistics (e.g., average scores for the different groups). Examples

Organizing Your Results Section: Step 4 4. Tell the reader whether the analysis supports your prediction, then back up this claim with both (a)the results of the statistical test and (b)descriptive statistics (e.g., average scores for the different groups). Examples

Logic of the Results Section: Sample Paper The first part of the sample paper (see Appendix B of your text) does not address the question: What do the scores that are being analyzed represent? The reason that it doesn't is because Frank and Gilovich explained what the scores represented in the last section of their method section (the Dependent Measure section.) Most authors do not have such sub-sections in their method section. Consequently, most authors wait until the results section to talk about how individual scores are derived. Notice what the authors of the sample paper do to make it easy on the reader. 1. They start by saying whether the results were consistent with their predictions. 2. They begin their support of this claim by presenting fairly simple statistics: averages. 3. They present a table so the reader can easily see all four means at the same time. 4. They wait to talk about the tests of statistical significance and interactions until after the reader knows what the pattern of means is. 5. They tell the reader what the test results indicate: They do not make the reader figure it out on his or her own. Use these strategies when you write your Results sections.

FORMAT OF THE RESULTS SECTION: Overview For the most part, the formatting rules that affect the rest of the paper affect the results section. However, points to pay special attention to in the result section include: Put tables and figures at the end of your paper. Don't label a graph Graph 1. Instead, label it Figure 1. Italicize abbreviations for statistics such as "t" and "F." Italicize "p " Put the degrees of freedom for a test in parentheses. To learn more about tables, go to the next page. Click here, to see examples of Results sections.

Results Section Format: Tables You do not put tables in the results section of the unpublished manuscript that you hand in. However, you must refer to the table in the text. The actual tables or figures come at the end of the paper. As you can see from the table at the end of the sample paper, everything is double spaced, the label Table 1 is flush left, and the title is flush left and italicized.

Sample Results Section Results Manipulation Check To determine whether the attractiveness manipulation worked, participants rated the attractiveness of the defendant on a 7-point scale, ranging from 1 (not at all attractive) to 7 (extremely attractive). An analysis of variance performed to assess the effects of the attractiveness manipulation on perceived attractiveness showed that participants in the attractive defendant condition rated the defendant as more attractive (M = 6.5), F (1,65) = 20.25, p <.001 than those in the unattractive condition (M = 2.4). Hypothesis Tests Participants recommended a prison sentence for the defendant. The length of these sentences were the scores that were analyzed by a between groups t test. I hypothesized that the attractive defendant would receive a lighter sentence than the unattractive defendant. In support of this hypothesis, the attractive defendant received a lighter sentence (M = 2.6) than the unattractive defendant (M = 4.8), F (1,65) = 6.12, p =.016.

Example of a Results Section Results The dependent variable was participants' responses to the question "How much would you be willing to spend for a ticket to a rock concert?" Scores on this variable were analyzed using a between-groups ANOVA. As hypothesized, experimental group participants were willing to spend more (M = 25.5, SD =3.5) than control group participants (M = 18.8, SD = 3.2), F (1,92) = 4.57, p =.035.

Example of a Results Section Results The data were analyzed using a between subjects ANOVA. As Figure 1 indicates, status influenced liking. More specifically, high status individuals (M = 6.02) were liked more than low status individuals (M = 3.81), F (1,28) = 8.02, p =.008.

END OF WRITING RESULTS SECTION TUTOR NOTE: THIS TUTORIAL IS ONLY FOR THE USE OF AUTHORIZED ADOPTERS OF Mark Mitchell's and Janina Jolley's text Research design explained (8th ed.). END

Example of Step 1 A depression index was constructed by adding the scores from questions 1 to 30. The results of this depression index were analyzed by a two- factor, between-subjects analysis of variance. For data analysis, we calculated a score by averaging the two observers ratings. These scores were then analyzed using a between- subjects t test. Go back

Example of Step 2 To examine the hypothesis that introverts would be more anxious than extroverts, we did a between groups t test. For data analysis, we calculated a score by averaging the two observers ratings. These scores were then analyzed using a between-subjects t test. Go back

Example of Step 3 The hypothesis that scores on the happiness scale would be higher for the treatment group than for the control group was supported. Specifically, the treatment groups average score on the happiness scale (M =5.45, SD =1.1) was significantly higher than the control groups (M = 3.98, SD=1.2), t (198) = 22.25, p <.001. Go back

Example of Step 4 This main effect was qualified, however, by the predicted humor X distractions interaction, F(1,36) = 5.16, p =.029. As can be seen from Table 2, in the no distraction conditions, participants in the humor condition scored higher than participants in the no humor condition (Ms =10.0 vs. 4.0). However, in the distraction conditions, participants in the humor condition scored lower than participants in the no humor condition (Ms = 3.0 vs. 8.0). We also found that … The results also indicated that … Go back

Similar presentations