Where Do I Find the Values for the
F-Statement? back to Experimental Homepage Recall that when you are writing up a results section you want
to cover
three things: Below you will find descriptive information and an analysis of variance summary table. This table is from an experiment that investigated whether physically attractive vs. unattractive defendants in a criminal case would be rated differently on amount of guilt (GUILTY) and length of prison sentence (PRISON). Because there is only one independent variable (attractiveness of the defendant), this analysis is referred to as a one-way analysis of variance. If there were two independent variables, then the analysis would be referred to as two-way analysis of variance.
A good results section for the analysis on guilt ratings would be: Results The effect size r
was calculated for all appropriate analyses (Rosenthal, 1991). Guilt Ratings (Margin headings are useful to tell the reader what the paragraph will be about. Format it correctly). A one-way analysis
of variance
(ANOVA) was calculated on participants' ratings of defendant guilt. The
analysis was not significant,
If the "Guilty" analysis had been significant, then it would be correct to describe the mean differences in the following manner:
Participants who read about an unattractive defendant rated
the defendant
more guilty ( attractive
defendant
( Try writing the results for the analysis on length of prison sentence ratings...I'll get you started. Length of Prison Sentence Ratings (Margin headings are useful to tell the reader what the paragraph will be about. Format it correctly). A one-way ANOVA was
calculated
on participants' ratings of length of prison sentence for the
defendant. The analysis was significant,
Once you understand the results from a one-way ANOVA, try to figure out a more sophisticated ANOVA by clicking here.
The information contained in the "
The information that comes after the "=" is the actual value
of that
Simple. All you need to do to determine whether that particular analysis is significant is to, again, look at the analysis of variance summary table under the "Sig." column. The "Sig." column is your probability level for that particular analysis. Remember, any value in this column that is LESS than .05 is significant. All other values in that column that are greater than .05 are NOT significant. But, I KNOW you remember all of this from your statistics class...right?
"
Below you will find descriptive information and an analysis of
variance
summary table. This table is from an experiment that investigated
whether
the type of music that song lyrics were attributed to would differently
impact whether participants thought the lyrics were objectionable
(OBJECT) and whether they thought
the lyrics should have a mandatory warning label (WARN). This analysis
differs from the one above, because the
independent
variable (type of music) has three levels. When you have an independent
variable that has three or more levels, then
you must run comparisons among the levels (e.g., country vs. rap,
country vs. heavy metal, rap vs. heavy metal) for
each of the dependent variables. The write-up for the lyric objection results could be as follows: Results The effect size r was calculated for all appropriate analyses (Rosenthal, 1991). Objection to the Lyrics A one-way analysis
of variance
(ANOVA) was calculated on participants' ratings of objection to
the lyrics. The analysis was significant,
heavy metal
( the country music condition , 1.58, To make sure you understand, you should write up the results
for whether the lyrics should have a mandatory warning label (WARN). Correlational Analyses Suppose we wanted to examine the
relationship between self-esteem and negative mood. First, we
should remember that scores on the Rosenberg self-esteem scale range
from 10 to 50 with higher scores indicating higher self-esteem.
The measure of negative mood ranges from 12 to 60 with higher scores
indicating more negative mood. We get 122 undergraduates to
complete both measures, enter the data, run the analysis, and get the
following:
How
do we write this up in a results section? Results
A
correlational analysis was conducted to examine the relationship
between
negative mood and self-esteem. The
analysis was significant,
r(122) =
-.49,p < .001. Participants
with higher self-esteem scores
reported less negative mood.Correlation
Statement Spacing
* Same spacing applies for F
statements. |