writing up results. results are divided into two main sections, usually descriptive statistics –...
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Writing up results
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Results are divided into two main sections, usually
• Descriptive Statistics– Include frequencies for nominal/categorical
variables– Include means and standard D for
continuous/ranked variables– Include # of missing (not items, but actual surveys
that could not be included)
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Some uncertainties
• Descriptive statistics (means, sd) are often compared to similar published data to see if they make sense.
• E.g. “CES-D scores had a mean of 8, SD of .79 in the current sample. This is similar to a same aged sample collected by Smith and Jones (2011).
• This kind of info can go in results or sometimes in discussion. I prefer it in results.
• You don’t have to include it, but if you do that is where I would like it.
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Where do the alphas go?
• Alpha tells us if folks answered questions consistently within the same scale
• The alphas go in the method section• Technically they are a “result,” but they go in
the method section at the end of the description of the measure.
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How do you calculate an alpha?
• In SPSS• Go to Analyze/Scale/Reliability Analysis• Select the items in the scale (use the reverse
scored items where relevant)• Analyze• Results show if your scale has good internal
consistency in this sample or not
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Results—substantive analyses
• If you have hypotheses, you can call this section “hypothesis testing”
• Otherwise you can call it “Research Questions”
• Looking at how other published articles do this is the simplest, fastest way to learn how to present these numbers.
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Results Section General Framework
• Results for each hypothesis can be divided into 3 general statements
• 1. What the test was, generally• 2. The actual variables and setup of the
analysis• 3. The numerical and substantive outcome of
the analysis
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1. mention the type of statistical test you used
• Like “We ran correlation analyses to determine if happiness total score was related to the number of reported facebook friends.”
• Or “We used analysis of covariance to determine if there were differences in food consumption by experimental or control group, after controlling for body image ratings.”
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Results sections
• Or• “We used correlation to determine if self-
reported frequency of drug use was related to perception of peer risk behavior.”
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2. Specify the variables and setup
• This will sometimes seem redundant to the previous statement. If so, you can leave it out or minimize it.
• Like “We calculated bivariate correlations between the total score for self reported drug use, and perception of peer drug use.”
• This is redundant. You could leave it out.
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2. Specify the variables
• It will not always seem redundant.• Like “We entered group membership
(experiment or control) as a predictor, and body image rating as a covariate. The dependent variable was ounces of unhealthy snack food consumed.
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2. Specify the variables
• Sometimes you will have repetition when you are doing analyses that are parallel.
• Like “We conducted a separate ANCOVA with the same predictor and covariate, and the dependent variable for this analysis was ounces of healthy snack food consumed.”
• Be sure to specify when the dependent or independent variables change for various analyses, even if they are related
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3. Give the numerical and substantive outcome
• The numbers will depend on your test. You need to include the statistic and the significance (p value, usually).
• E.g. for a correlation: “self perceived drug use and perception of peer drug use were significantly positively related: r = .14, n=78, p=.04.”
• Or “Happiness totals and intensity of facebook use were significantly negative correlated: r=-.20, p=.03.”
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…numerical and substantive outcome
• If you are presenting ANOVA, ANCOVA or T tests you will also need to include the degrees of freedom.
• E.g. “There was a main effect for group membership, such that members of the experimental group were less likely to consume unhealthy snacks: F=3.22 (1, 68), p=.02. Means and standard deviations are presented in Table X.
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Numerical and substantive outcome
• In a real paper you do not report the numbers for non-findings
• In this paper I would like you to report the numbers for non-findings
• Also note that statistics such as r, t, F, and p are italicized in apa style.