In-Class Research Report 3: Experimental Study
? One paragraph about the ?design.
(Joceline)
This is a posttest-only between-subjects experiment that will be measuring the
causation of playing on aggression. Playing being our independent variable, was broken
down to three levels: solo, cooperative, and competitive. A constructed basketball game
was intervened by timing our participants ability to shoot basketballs inside a basketball
hoop. And a survey that was given to our participant after the basketball game is our
posttest . This helped us measure our dependent variable, aggression.
? This section will be a little more complicated than the previous
studies. You should be able to explain *what type* of
experiment you’re conducting (between vs. within subjects?
Pretest-posttest vs. posttest-only?). In addition, you should
be appropriately labeling the different levels of your
independent variable, as well as the IV and DV themselves.
? One paragraph about the ?participants?.?Alexis
? Who were your participants, and how were they selected (i.e., what
was your ?sampling strategy?)? In order to describe who you
actually ended up with, you should include any relevant
demographic information here, such as ages and genders, as well
as the total number of participants.
Our sample population consisted of males and females found at any park around
our communities. Each group member went to a local park with a basketball court, and
asked every other person they saw playing basketball. Each group member was to get
6 participants, 2 to play solo, 2 to play cooperative, and 2 to play competitive. We ended
up with a total of 43 participants (N=43). We did not have demographic questions on our
survey so we have no data pertaining to the age or gender of our participants. 15 of our
participants (34.9%) played competitively. 14 participants (32.6%) played solo. 14
participants (32.6%) played cooperatively.
? 1-3 paragraphs about your ?measures?. ?Amir & Joceline
Our group wanted to answer the question, does playing reduce aggression? We
defined aggression as someone who is confrontational or demonstrates violent
behavior. The two variables examined in this study were playing and aggression,
playing being our independent variable and aggression being our dependent variable.
We were able to manipulate our independent variable by creating a basketball game
and broke it down to three counterparts: a solo game, a cooperative game, and a
competitive game. In a solo game a participant was given 30 seconds to make 15
hoops from the free-throw line. In a competitive game 2 participants would race against
each other to shoot the most balls in the basketball hoop within 30 seconds, also from
the free-throw line. And in a cooperative game 2 participants would attempt to make 15
hoops together from the free-throw line within 30 seconds.
To measure our dependant variable we constructed an online survey that was
given to them when the game was over. This allowed our participants to let us know
how angry they felt while playing. A numerical value was assigned to each response
option: Not at all = 1, Maybe = 2, Most likely = 3, Yes =4 . We then added up their
points, the participant with the highest survey score represented high levels of
aggression. A participant with a low survey score represented low levels of aggression
while playing.
? Considering the variable that was being studied, you should be
able to clearly explain how it was measured.
? For this section especially, you should be prioritizing
replicability?–you should be providing enough information that
someone else could read about your study and conduct as close to
the same study as possible. What would they need to know in
order to do that?
? Remember that you’re only measuring your DV. You will
explain how the IV was manipulated in the next section.
? 1-3 paragraphs about the ?procedure?.?Yasi & Sheryn
? This should be a narrative: in a step-by-step description, how did
you conduct the study? (You can start from the point ?after? you’ve
selected a participant–your sampling strategy should already be
described in the Participants section.) What, exactly, did you and
your participants do at each step of the way?
? This should be a ?general? explanation of your procedure–please
don’t re-write this for every single participant. However, if there
were any noteworthy or unexpected things that occurred with any
of your participants, you can note them here.
? Make sure to explain how the study proceeded differently in
the different conditions of the IV. Also, make sure that you
explain how your participants were assigned to the different
conditions.
(Sheryn )
As a group we decided to see if aggression is reduced by playing games.
We each asked about six participants at the park; for the sake of
convenience sampling. Each participant is given fifteen chances to shoot
the ball into a basketball hoop, during this time, each conductor is
observing the participant for reactions during the game such as happy,
upset, disappointment, frustration, cursing, taunting, etc. Participants were
grouped into three different categories of basketball playing. (1)
Solowhere the participant gets fifteen chances to try and shoot a
basketball into a hoop by themselves, (2) Cooperativewhere two
participants team up together and try to get as many basketballs into the
hoop for a max score of 30 points, (3) Competitivewhere two
participants get 15 chances to see who score the most into the hoop. The
categories were given to participants in order; one solo participant , two
cooperative participants , two competitive participants until we had 31
participants.
? One paragraph about ?data analysis?.?Jyoti
The variables we measured to answer our research question included the scores
on the self-report survey for aggression. Aggression being our dependent variable and
playing being our independent variable. We divided our independent variable (playing)
into three levels: Solo playing, Cooperative playing, and Competitive playing. We
measured the mean and standard deviation for each level of our independent variable.
In addition we conducted the One-Way Anova for Independent measures to determine
whether there was a statistically significant difference between the means of the three
levels of our independent variable. We used the website Social Science Statistics to
calculate the One-way ANOVA calculator for independent measures.
? Before? you look at the data, explain what variables you will
analyze, and what statistical tests you will conduct. ?Why? are you
conducting these tests?
? If you performed any operation on your data, such as adding or
taking an average of responses to multiple questions, you should
describe this here.
? For this study, you will again be providing descriptive
statistics. In this case, however, you should be providing the
M and SD for the DV for each of your conditions of the IV.
? To compare these means, start with an ANOVA comparing all
three. This may be independent- or dependent-means,
depending on whether your experiment is between- or
within-subjects. *If* this test is statistically significant, you
should follow up with post-hoc comparisons–separate
ANOVAs (or t-tests) comparing just two means at a time. For
these post-hoc tests, you should use a corrected alpha level;
divide .05 (our desired alpha) by the number of post-hoc tests
you’re conducting, and compare the p values for these tests to
that value. (If the overall ANOVA is non-significant, you can
skip the post-hoc tests.)
? 1-2 paragraphs about the ?results?. ?Victor
? What were the data, and what do they say about your hypothesis?
You should be providing relevant descriptive statistics, results of
statistical tests, and a plain English description of what they mean.
? See Reporting Statistics below for examples of how to write up
specific statistical tests.
? In general, if you measured something, you should be reporting the
outcome here. Also, your results should correspond with the plan in
the previous section.
? Any ?appendices? (such as questionnaires, pictures, etc. that were used in the
study) should come at the end.
Reporting Statistics
? Commonly used abbreviations:
? N = number of participants (or observations), M = mean, SD =
standard deviation, ?p? = probability value
? ANOVA example:
? There was an observed difference in number of puzzles solved
based on the room to which participants were assigned, ?F (? 2, 42) =
13.49, ?p ?=.000. Post-hoc t-tests showed that participants in the
green room solved significantly more puzzles (M =10.39, SD =
2.86) than those in the yellow room (M = 4.87, SD = 2.98), ?t? (48) =
-5.17, ?p? = .000. Those in the orange room also solved more
puzzles (M = 8.11, SD = 2.93) than those in the yellow room, ?t? (48)
= -3.001, ?p? = .006. Numerically, participants in the green room
solved more puzzles than those in the orange room, ?t? (48) = 2.156,
p ?= .040, but with a Bonferroni corrected a value of .017 this
difference was no longer significant.
Particpants
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Mean:
SD:
N
?X
Mean
?X2
Std.Dev.
Solo Play Score (IV 1)
6
8
10
6
6
9
12
9
15
11
8
9
11
11
6
6
8.9375
2.644963768
IV 1
16
143
8.9375
1383
2.645
Cooperative Play Score (IV 2) Competitive Play Score (IV 3)
6
6
6
6
6
7
6
6
10
21
9
12
9
9
7
15
10
20
9
14
10
11
10
9
9
8
13
9
13
10
9
12
8.875
10.9375
2.247220505
4.625563029
Summary of Data
Treatments
IV 2
16
142
8.875
1336
2.2472
Result Details
IV 3
16
175
10.9375
2235
4.6256
Total
48
460
9.583
4954
3.4073
Source
SS
df
Between-treatments
44.0417
2
Within-treatments
501.625
45
Total
545.6667
47
The f-ratio value is 1.97546. The p-value is .150544. The result is not significant at p < .05.
MS
22.0208
11.1472
F = 1.97546
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