Description
Results Section: I expect the following format (15 points) —hard to set page limit for this
section because you are strictly required to have 3 analyses.
a. The results are the hardest part of this paper, and your lab will help you with this part of
the paper. But this section is the most standardized part.
b. First, write Results at the top of this section, center it, and use boldface. This section
comes directly at the end of the Method section, so the results section DOES NOT start
on its own page.
c. For this assignment, include statistics about the most important variables in your study,
including your IV (Type of Apology – Sincere, Insincere, and No Apology) and the
DVs (here, I require Part V (manipulation check), Part II Q1 Wrong, and Part II Q7
Sincere.
d. For this paper, you must run at least three different analyses (that is, focus on three
different dependent variables). One must be a chi square for Part V, our manipulation
check. One must be a one-way ANOVA on Part III Q1 Wrong. The last one must be
one-way ANOVA on Part II Q7 Sincere. Please note that if you run three tests on the
YOUR SHORT TITLE 5
same DV, that still only counts as one DV, you will lose points. We count the number
of DVs you analyze – NOT the number of tests you run!
i. Chi square: Your first analysis will be a chi square, which you use if your DV
is categorical (yes / no; yes / no / maybe; male / female, or … in our case, we
have Recall the apology on last question). So, let’s discuss the chi square, which
does not look at means but rather counts how many responses there are
compared to how many you would expect.
1. Consider DV last question on your questionnaire – “what hashtag did
Charlie end the Twitter post with?” Here, you can run a chi square
looking at the frequencies of the three answer options
2. We are interested in the chi square (χ
2
) and p value. We also provide
percentages for each of our groups (rather than means and SD).
a. “Using the type of apology primed on Facebook page (sincere vs.
no apology vs. insincere) as independent and recall of hashtag
Charlie ended the post with as the dependent variable, Chisquare test had a significant results, χ
2
(1) = 68.49, p = .031
(directly report p value, however, if SPSS output shows p
=.000, then write p < .001). Most participants in the sincere
condition recalled #SorrySorrySorry (98.45%); most participants
in the no apology condition recalled #WhatDoneIsDone
(96.02%); and most participants in insincere condition recalled
#SorryNotSorry (90.69%). This indicates that participants saw
our manipulation as intended.”
b. Make sure to round up to 2 decimals (except for p), italicize the χ
and p.
ii. ANOVA: Since you have a condition independent variable with three levels, the
most appropriate test is a One-Way ANOVA if your DV is scaled (like a 1 to 9
scale or a 1 to 6 scale). Your lab will show you how to conduct an ANOVA, but
there are some guidelines I want to give you about how to write your results.
1. First, for my example analysis below, I want to give you an example on
Charlie’s apology acknowledged the behavior was wrong.
2. We look first at the ANOVA table (or F table) and focus on the between
subject factor. We note the degrees of freedom, the F value itself, and
the p value.
3. If the p value is significant (less than .05), we have one more step to
take. Since this is a three level IV, we need to compare mean A to mean
B, mean A to mean C, and mean B to mean C. We do this using a Tukey
post hoc test. That will tell us which of the means differ significantly.
You then write up the results (Note: I completely made up the data
below).
a. “Using the type of apology primed on Facebook page (sincere vs.
no apology vs. insincere) and ratings of Facebook user’
warmness as the dependent variable, One-way ANOVA had a
significant result, F(2, 203) = 4.32, p = .02. Tukey post hoc tests
showed that participants agreed more strongly that the apology
showed the acknowledge of wrongfulness in sincere condition
YOUR SHORT TITLE 6
(M = 5.56, SD = 1.21) than those in insincere (M = 4.24, SD =
0.89) and no apology (M = 4.23, SD = 0.77) conditions. The
insincere and no apology conditions, however, did not differ
from each other. This supports the prediction that the way people
apologize influences how other people feel about the apology.”
i. Note there are three possible outcomes: NONE of the
three conditions differ (A = B = C). ALL differ from each
other (A ≠ B ≠ C). One differs from the other two, but
those other two do not differ (A ≠ B = C). You need to
write out the results based on your analysis results.
b. Make sure to round up to 2 decimals (except for p), and italicize
the F, p, M, and SD (as in the example)
c. Now you can run and write out the same ANOVA on our DVs
(Part II Q1, Part II Q7)
RUN THREE TESTS: One must be a chi square for Part V, our manipulation
check (WITHOUT LOOKING BACK, WHAT HASHTAG DID CHARLIE END THE TWITTER POST WITH?), One must be a one-way ANOVA on Part III Q1 Wrong ( SECOND PART OF THE SURVEY), The last one must be
one-way ANOVA on Part II Q7 Sincere (FIRST PART OF THE SURVEY).
study will be attached *** There are three different surveys: only thing that changes really is the very last Tweet : whether he apologizes or not and the hashtag he used. PLEASE READ 3 STUDIES FIRST AND INSTRUCTIONS ON HOW THE STUDY WAS COMPLETED.
I WILL ATTACH THE TABLES THAT I COMPLETED.