You will be reporting three or four
things, depending on whether you find a significant result for your 1-Way
Betwee Subjects ANOVA
You want to tell your reader what
type of analysis you conducted. This will help your reader make sense of
your results. You also want to tell your reader why this particular analysis
was used. What did your analysis test for?
You can report data from your own
experiments by using the template below.
“A one-way between subjects ANOVA
was conducted to compare the effect of (IV)______________ on (DV)_______________
in _________________,
__________________, and
__________________ conditions.”
If we were reporting data for our
example, we might write a sentence like this.
“A one-way between subjects ANOVA
was conducted to compare the effect of sugar on memory for words in sugar, a
little sugar and no sugar conditions.”
You want to tell your reader whether
or not there was a significant difference between condition means. You can
report data from your own experiments by using the template below.
“There was a significant (not a
significant) effect of IV ____________ on DV ______________ at the p<.05
level for the three conditions [F(___, ___) = ___, p = ____].
Let’s fill in the values. You are
reporting the degrees of freedom (df), the F value (F) and the Sig. value
(often referred to as the p value).

You have a sentence that looks very
scientific but was actually very simple to produce.
“There was a significant effect of
amount of sugar on words remembered at the p<.05 level for the three
conditions [F(2, 12) = 4.94, p = 0.027].”
In the previous chapter on
interpretation, you learned that the significance value generated in a 1-Way
Between Subjects ANOVA doesn’t tell you everything. If you find a
significant effect using this type of test, you can conclude that there is a
significant difference between some of the conditions in your experiment.
However, you will not know where this effect exists. The significant
difference could be between any or all of the conditions in your experiment.
In the previous chapter, you learned that to determine where significance
exists you need to conduct a post hoc test to compare each condition with
all other conditions. If you have an IV with 3 levels, like the one in this
example, you would need to conduct and report the results of a post hoc test
to report which conditions are significantly different from which other
conditions.
Because we have found a
statistically significant result in this example, we needed to compute a
post hoc test. We selected the Tukey post hoc test. This test is designed to
compare each of our conditions to every other conditions. This test will
compare the Sugar and No Sugar conditions. It will also compare the A little
sugar and No Sugar conditions. It will also compare the A Little Sugar and
Sugar conditions. The results of the Tukey post hoc must be reported if you
find a significant effect for your overall ANOVA.
You can use the following template
to report the results of your Tukey post hoc test. Just fill in the means
and standard deviation values for each condition. They are located in your
Descriptives box.

If you used this template with our
example, you would end up with a sentence that looks something like this.
“Post hoc comparisons using the
Tukey HSD test indicated that the mean score for the sugar condition (M =
4.20, SD = 1.30) was significantly different than the no sugar condition (M
= 2.20, SD = 0.84). However, the a little sugar condition (M = 3.60, SD =
0.89) did not significantly differ from the sugar and no sugar conditions.”
Since it might be hard for someone
to figure out what that sentence means or how it relates to your experiment,
you want to briefly recap in words that people can understand. Try to
imagine trying to explain your results to someone who is not familiar with
science. In one sentence, explain your results in easy to understand
language.
You might write something like this
for our example.
“Taken together, these results
suggest that high levels of sugar really do have an effect on memory for
words. Specifically, our results suggest that when humans consume high
levels of sugar, they remember more words. However, it should be noted that
sugar level must be high in order to see an effect. Medium sugar levels do
not appear to significantly increase word memory.”
This sentence is so much easier to
understand than the scientific one with all of the numbers in it.
When you put the three main
components together, results look something like this.
“A one-way between subjects ANOVA
was conducted to compare the effect of sugar on memory for words in sugar, a
little sugar and no sugar conditions. There was a significant effect of
amount of sugar on words remembered at the p<.05 level for the three
conditions [F(2, 12) = 4.94, p = 0.027]. Post hoc comparisons using the
Tukey HSD test indicated that the mean score for the sugar condition (M =
4.20, SD = 1.30) was significantly different than the no sugar condition (M
= 2.20, SD = 0.84). However, the a little sugar condition (M = 3.60, SD =
0.89) did not significantly differ from the sugar and no sugar conditions.
Taken together, these results suggest that high levels of sugar really do
have an effect on memory for words. Specifically, our results suggest that
when humans consume high levels of sugar, they remember more words. However,
it should be noted that sugar level must be high in order to see an effect.
Medium sugar levels do not appear to significantly increase word memory.”
Looks pretty
complicated but it is simple when you know how to write each part.
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