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Research Methods
APA Ethical Guidelines

Human Drug Trials
 The
APA – American Psychological
Association
 Responsible for setting the ethical
guidelines for human and animal
research.
 The
IRB – Institutional Review Board
 Part of the APA responsible for
reviewing research proposals for
ethical violations and/or procedural
errors.
Human Research
Research
involving human
subjects must meet the
following standards:
1.
Informed
Consent
–Participants must
know that they are
involved in research
and give their
consent.
2.
Coercion
–Participation in
a research study
must be
voluntary.
 3.
Anonymity/Confidentiality
–The participant’s privacy must
be protected. No identities and
actions may be revealed. A
researched must not share any
results that could match a
participant and their specific
responses. A researcher will
not identify the source of any
data as well.
4.
Risk
–Participants cannot
be placed at any
significant mental
or physical risk.
5.
Debriefing
Procedures
–Participants must be
told the purpose of the
study and provided
with ways to contact
the researcher about
the study results.
Animal Research
Ethical
studies using laboratory
animals must meet the
following requirements:
1.
The must have a clear
scientific purpose.
–The research must
answer a specific,
important scientific
question. Animals are
chosen based on their
ability to help answer the
question proposed.
2.
The animals
must be cared for
and housed in a
humane way.
3.
The animal subjects
must be acquired in a legal
manner.
–The animals used in the
experiment must be
purchased from accredited
companies, and if trapped in
the wild, they must be
trapped in a humane
manner.
4.
The experiment
must be designed
with procedures in
place that employ the
least amount of
suffering on the part
of the animals.
How do
psychologists
collect data about
behavior?
Regardless
of the method
used, all research is based
on the Scientific Method of
Psychology
 Scientific
means systematic,
testable, and objective.
What are the main
principles that
guide the Scientific
Method of
Psychology?
 Step
 Step
 Step
 Step
 Step
 Step
1 – Review the existing
Literature
2 – Develop a testable
Hypotheses
3 – Research and Observation
4 – Analyze the data
5 – Publish, Replicate, Seek
Review
6 – Build a Theory
Step 1
Review
the existing literature.
What studies have already
been completed? What are
the current theories and data
indicating about behavior?
Step 2
A
hypothesis is then created
as a testable prediction based
on what is currently known
and what we want to find
out. What do we want to
know more about?
Step 3
Experiments,
surveys,
observations, casestudies, etc. are
generated to collect
data.
Step 4
 The
raw data is organized and
needs to be evaluated. Statistics
may be used to organize,
summarize, and interpret the
numerical data. Does the data
support, or not support, the
hypothesis?
Step 5
 The
results should be shared with
other researchers in a peer-reviewed
journal. Other researchers may
choose to replicate (repeat) the study
to check for validity, or to further
explain or explore some aspects of
the study.
Step 6
After
one or more studies on a
given topic, researchers may
advance a theory (current
knowledge/concepts that
explain a body of data), or
challenge a theory.
What are the two
broad types of
research that
psychologists
conduct?
Research Designs
Quantitative
and
Qualitative Research
Quantitative
.
Research usually
involves experimentation or
correlation studies, and the
data produces numbers,
measurements, deductive
logic, statistics, etc.
Qualitative
Research
emphasizes natural settings
and observation, and
generates data in the form of
written themes, verbal
narratives, personalized
comments, pictures, etc.
What are examples
of a qualitative
research methods?
I. Naturalistic Observation
 Researchers
study
spontaneous and
natural behaviors in
a subjects most
familiar environment.
There is no
interaction with the
subject during these
observations.
Researcher Bias
Situation
in which a
personal factor unfairly
increases the likelihood
of a researcher reaching a
particular conclusion
Example of Bias
I was recently mugged by a group
of teenagers, or I just had a fight
with my teenage son over driving
privileges. My assignment is to
observe teenage behaviors at the
mall. Will I be more inclined to
seek out bad behaviors or infer
bad intentions and motivations?
Participant Bias
The
tendency of research
subjects to respond in certain
ways because they know they
are being observed. The
subjects might try to behave in
ways they believe the
researcher wants them to
behave.
 The
Hawthorne Effect refers to
the fact that some subjects will
alter their behaviors simply
because they know that they are
part of an experiment, regardless
of what is being done to them.
II. Case Study
A
case study is a situation in which
a single individual is studied indepth by a researcher, often times
due to their unique behaviors or
situation. Case studies are very
interactive and often include faceto-face interviews, paper and
pencil tests, the study of medical
records, etc.
Police
have arrested Bart for
the serial killing of fifteen
young women over the past
ten years. A psychiatrist will
examine the police files,
medical files, observe and
interview Bart, talk to his and
the victims families, friends,
etc. in order to understand
Bart’s behaviors and
motivations.
What is the best
example of a research
method that produces
both quantitative and
qualitative data?
III. Survey
 Questionnaires/
interviews.
Using a combination of forced
and open response questions, it
can be helpful in analyzing and
predicting behaviors.
 Advantageous because you
gather a large amount of
information from a large group
of people.
False Consensus Effect
 Tendency
to overestimate the
extent to which others share
our beliefs and behaviors.
Skews the reports by jumping
to large conclusions that fit
into our pre-conceived ideas.
Which types of
research produce
primarily
qualitative data?
IV. Experiment
 An
investigation seeking to
understand relations of cause and
effect. The experimenter changes a
variable (cause), and in turn
changes another variable (effect).
At the same time the experimenter
hopes to hold all of the other
variables constant so that they can
attribute any changes to only the
manipulation.
 IE.
I want to know if new Drug A will
help to alleviate the symptoms of
insomnia. I can manipulate the dosage
and the times, but I need to control
other factors like mattress softness, diet
and room temperature to eliminate
them as variables that affect sleep. At
the end of the experiment I want to
know that it was only Drug A that
affected the patient’s sleep.
How do I
create a
valid and
reliable
experiment?
Step 1: Choose a Hypothesis
A
hypothesis expresses a
relationship between two
variables.
 IE.
My hypothesis is that
watching violent television
programs makes people more
aggressive.
Step Two: Choose Variables
Variables
are things
that are measured,
controlled, or
manipulated in
research.
The
independent
variable is the
manipulated variable
.
IE.
The violent
programming is the
independent variable
because I can adjust what
shows are viewed, for how
long, by whom, etc.
The
dependent variable is
measured for change.
IE.
Measuring the change in
aggression levels is the
dependent variable in our
experiment because it changes
based on what is viewed, for
how long, etc.
Step Three: Operationalize
When
you operationalize
your variables, you are
explaining how you will
measure them.
 IE.
The operational definition of the
independent variable (what defines a
violent show?) would be shows that
have scenes of fighting, bloodshed, use
of weapons, injury, kicks, punches, etc.
 IE. The operational definition of the
dependent variable (what constitutes an
increase in aggressive behavior?) would
be an increase in agitation or
tenseness, increased vocal volume,
threats of bodily harm, kicks, punches,
throwing objects, etc.
Step Four: Identify Potential Extraneous
Variables/Confounding Variables
 It
is important to make sure that
during the experiment as many
other factors that are NOT part of
the therapy are NOT included. Any
factor or variable that causes an
effect (or potential affects) other
than the variable being studied is
considered an extraneous variable.
 IE.
An extraneous variable in our
experiment would be a phone call
from a solicitor during a program,
the viewer receiving mail including
a poor report card, a viewer
stubbing their toe during a show,
alcohol abuse, etc. All of these
could increase aggressiveness, but
are not related to viewing violent
television.
Step Five: Identify Who You Will Be Testing
The
people on which the
research will be conducted
are called participants. If
you are using animals, they
are referred to as subjects.
–I want to test the effects of
television violence on
teenage behaviors.
Step Six: How Do We Decide Who
Will Be Subjects, and Who Won’t?
Since
we can’t realistically test
all teenagers in the world (the
test population), we must
reduce the overall population
down to a more manageable
number (the test sample).
How?
Method 1: Rigorous Control Design
Designing
an experiment with
specific, hand-picked
participants in mind.
–IE. Only testing males, 18
years old, enrolled in AP
Psychology at Middletown High
School.
Method 2: Random Sample
A
random sample allows
that every member of an
overall population has an
equal chance to be in the
sample.
 IE.
Put all teenager’s names into
a hat and pull out fifty names.
Method 3: Systematic Sample
 Select
a starting point from your
population and then select every ?th
participant.
– Alphabetically list all teenagers from one
to one million, and then choose every
10th name on the list to be a participant
in the experiment.
Step Seven: Assignment
Once
you have chosen your
subjects to study, you must
assign them to one of two
groups; those that will be
manipulated, and those that
won’t.
Group 1: Experimental Group
The
experimental group
receives the
independent variable
and is manipulated
throughout the
experiment.
 IE.
In our television violence
experiment, those in the
experiment group will watch
varying degrees of violent
program, for varying lengths of
time, etc., and their changes in
levels of aggression measured.
Group 2: Control Group
The
control group
does not receive the
independent variable.
They are the used for
comparative
purposes.
 IE.
In our television violence
experiment, the control group will
be shown a variety of non-violent
programming in order to create a
baseline to compare the
experiment group against.
 How do the behaviors of teens
exposed to non-violent
programming compare with those
of teens who watch violent
programming?
Random Assignment
 Random
assignment means that
the subjects have an equal
chance of being placed into each
group. If we allow subjects to
choose their own group, we may
have a subject-relevant
confounding variable.
Subject-Relevant Confounding
Variables
A
subject-relevant confounding
variable would allow those people
that liked violent movies or were
prone to violence already to choose
to be in the experimental group. We
therefore could not accurately find
that viewing violence directly led to
their aggression.
To
help avoid this
confounding variable, we
prescribe a single-blind
design. The subjects do
not know whether they
have been randomly
placed in the control or
experiment group.
Group Matching
 When
assigning members to
the experiment or control
group, it is important that the
characteristics of both groups
need to be as similar as
possible.
IE.
After rigorously or
randomly determining our
subjects, as many white,
black, tall, short, overweight,
slim members should be in the
control group as there are in
the experiment group.
Experimenter Bias

Experimenter Bias occurs when the
experimenter unconsciously treats members of
the control and experiment groups differently,
which increases the chances of confirming their
hypothesis.

IE. The experimenter gives soda to the control
group, and beer to the violent viewers. The
experimenter speaks more abruptly with the
violence crowd (inciting them?).

To help avoid this type of
confounding variable, we
employ a double-blind
design, where neither the
subjects nor the researcher
may know which is the
control or the experiment
group. A third-party has the
appropriate records so that
the date can be analyzed
later.
Other Things to Consider…
The
Placebo Effect refers to
the phenomenon that a
patient's symptoms can be
alleviated by an otherwise
ineffective treatment,
apparently because the
individual expects or believes
that it will work.
Hindsight
Bias is the
tendency to believe, once
the outcome is already
known of course, that you
would have foreseen
it…that even though it's
over and you know the
outcome, you knew it all
along.
REMEMBER !!!
Only experimental data can
conclusively demonstrate
causal relations between
variables
(A causes B to happen).
Correlation
Correlation Study
Research
study designed to
determine the degree to
which two variables are
related to one another. This
does not prove a cause and
effect relationship; only that
some relationship exists.
 How
are exercise and
weight related? Are
smoking and rates of
cancer related? Is there a
relationship between brain
size and intelligence?
Does your level of
education have any
implications on your
potential future earnings?
Types of Correlation
Relationships
After you’ve
collected your data,
it’s time to organize
and analyze it.
Scatter
plots consist of a
large body of data plotted on
a graph to show their
relationship to one another.
The closer the data points
are to making a straight line,
the higher the correlation
between the two variables, or
the stronger the relationship.
Positive Correlation
As
the value of one
variable increases so
does the value of the
other variable.
 Studying
and Grades
–As students study more, their grades
increase.
 Practice
and Athletics
–As athletes practice more, their
batting averages increase
 Driving
Speed and Distance
–As drivers drive faster, they travel
further.
A
perfect positive
correlation results in a
numerical value of 1.00
Positive correlations range
from 0.00 to 1.00. The
closer to 1.00 you get, the
stronger the positive
correlation is.
Negative Correlation
As
the value of
one variable
increases, the value
of the other
variable decreases.
–The more you exercise, the
less you weigh
–The more you study, the less
your teachers yell at you
–As the price of movie tickets
increases, the number of
patrons decreases.
A
perfect negative
correlation results in a
numerical value of -1.00
Negative correlations
range from 0.00 to 1.00. The closer to -1.00
you get, the stronger the
negative correlation is.
Zero Correlation
There
is no relationship
whatsoever between the two
variables.
–The length of your hair has
no influence on your level of
intelligence.
No
correlation relates
to a numerical score
of 0.00
Correlation Study
 Important
NOT to imply a cause and
effect relationship between the
variables
 Correlational study does not
determine why the two variables are
related--just that they are related.
 Correlational studies are helpful in
making predictions.
Illusory Correlation

http://www.mensfitness.com/sports/athlet
es/10-most-superstitious-athletes
Once I have
completed my
research, how do I
present my findings ?
Descriptive
Statistics
describe a set of data.
I. Measures of Central Tendency

Measures of central tendency provide statistics
that indicate the average or typical score in the
distribution. There are three measures of central
tendency:
Mean
Median
Mode
Mean
The
mean is the
arithmetic average of all
the scores in the
distribution.
Regression to the Mean
 In
statistics, it is the phenomenon
whereby members of a population
with extreme values on a given
measure for one observation will
probably give less extreme
measurements on other occasions
when they are observed.
– IE. A running back rushed for 276 yards in
his first football game of the season. More
than likely he will not rush for 4416 yards that
season (considering only five players have
ever rushed from more than 2,000 yards in a
single NFL season). It’s more likely that his
game totals will decrease and his overall
average will eventually reflect an NFL average
of about 67 yards per game.
Median
 The
median is the middle score
of the distribution, the point that
divides a rank-ordered distribution
into halves containing an equal
number of scores. Thus 50% of
the scores lie below the median
and 50% lie above the median.
Mode
The
mode is simply the
score in the distribution
that occurs most
frequently.
Graphing Measures of Central
Tendency
Positively Skewed

This distribution has a positive skew.
Note that the mean is larger than the
median.
IE.
In a neighborhood of
relatively low incomes, a few
millionaires move in. Those
few high salaries will inflate
the mean (average), but the
median will remain relatively
low.
Negatively Skewed

This distribution has a negative
skew. The median is larger than the
mean.
IE.
In a particular well-to-do
neighborhood, a few lowincome residents move in.
The overall average income
will drop a bit, but the median
will remain relatively high.
When
graphing the mean,
median and mode of a
distribution, roughly
speaking, a distribution has
positive skew if the right
tail is longer and negative
skew if the left tail is
longer.
II. Measures of Variability
Measures
of variability
show how spread out the
distribution of scores is
from the mean.
Measures of Variability
Range
Standard
Deviation
Range
The
range is simply the
numerical difference
between the highest and
lowest scores in the
distribution.
Standard Deviation
 The
measure of variability used
most often in research is the
standard deviation, a statistic
that indicates the average
distance of the scores from the
mean of the distribution.

IE. Our class took Unit Exam 2. I scored
a 76%. I want to know how well I did in
relation to the rest of the class to see
whether or not that score was good or
bad. I need to figure out what the class
average was, figure out the standard
deviation from the mean, and I’ll know
how well I did.
Standard Deviation
Graphing Standard Deviation
Find the mean of your distribution set.
 Calculate the SD on your calculator.
 The mean is set at “0”.
 +1 and -1 are your SD above and below
the mean.

– IE. Your mean is 56 with a SD of 6. +1
would be 62, and -1 would be 50.
– Calculate +- 2 and +- 3 in the same manner.
Graphing Standard Deviation

What does this tell us?
– If the mean of a set of class scores on a unit
exam was 72, with a SD of 8, 68% of
students scored between a 64 and an 80.
Your score of a 76 would be close to being
better than 68% of the rest of the class.
– Approximately 95% of the class scored
between a 56 and an 88. Your score of a 50
would indicated that roughly 96% of the class
did better than you on the test.