psychological re

1. What is Science?
Science is the pursuit and application of
knowledge and understanding of the
world following a systematic
methodology based on evidence.
-Objective
-Evidence based research

2. WHY IS RESEARCH IMPORTANT?
Some of our ancestors, across the world and
over the centuries, believed that
trephination—the practice of making a hole
in the skull, as shown here—allowed evil
spirits to leave the body, thus, curing mental
illness and other disorders
Thought Experiment: Aura Reading
•Research is a mandatory process in:
• Validating Claims
• Disproving Claim
• Without research, we would only have
intuition, evidence lacking assumptions, and wild
claims.
Question: Is Psychology a science?

3. Scientific Attitude Part 1: Curiosity
Definition:
always asking new
questions

4. Scientific Attitude Part 2: Skepticism
Skepticism, like curiosity, generates
questions: “Is there another
explanation for the behavior I am
seeing? Is there a problem with how
I measured it, or how I set up my
experiment? Do I need to change my
theory to fit the evidence?”
Definition:
not accepting a ‘fact’ as true without
challenging it; seeing if ‘facts’ can
withstand attempts to disprove them

5. Scientific Attitude Part 3: Humility
Humility refers to
seeking the truth
rather than trying to
be right; a scientist
needs to be able to
accept being
wrong.

6. “Think critically” with
psychological science…
does this mean “criticize”?
Critical thinking refers to a
more careful style of forming
and evaluating knowledge
than simply using intuition.
Along with the scientific method,
critical thinking will help us develop
more effective and accurate ways to
figure out what makes people do,
think, and feel the things they do.
Why do I need to
work on my thinking?
Can’t you just tell me
facts about
psychology?
•The brain is designed
for surviving and
reproducing, but it is
not the best tool for
seeing ‘reality’ clearly.

7. Critical thinking:
analyzing
information,
arguments, and
conclusions, to
decide if they make
sense, rather than
simply accepting it.
Look for
hidden bias,
politics,
values, or
personal
connections.
Put aside
your own
assumptions
and biases,
and look at
the
evidence.
See if there
was a flaw in
how the
information
was
collected.
Consider if
there are
other
possible
explanations
for the facts
or results.

8. How Psychologists Ask and Answer
Questions:
The Scientific Method
The scientific method is the process of
testing our ideas about the world by:
If the data doesn’t fit our ideas, then we modify our
hypotheses, set up a study or experiment, and try
again to see if the world fits our predictions.
TOPHAT question 3

9. Some research findings revealed by
the scientific method:
Scientific Method: Tools and Goals
The basics:
 Theory
 Hypothesis
 Operational Definitions
 Replication
Research goals/types:
 Description
 Correlation
 Prediction
 Causation
 Experiments

10. Theory: the big picture
Example of a
theory: “All
ADHD symptoms
are a reaction to
eating sugar.”
A theory, in the
language of
science, is a set of
principles, built on
observations and
other verifiable
facts, that explains
some phenomenon
and predicts its
future behavior.

11. Hypotheses: informed predictions
“Testable” means that
the hypothesis is
stated in a way that
we could make
observations to find
out if it is true.
A hypothesis is
a testable
prediction
consistent with
our theory.
What would be a
prediction from the “All
ADHD is about sugar”
theory?
One hypothesis: “If a kid gets sugar, the kid will act more
distracted, impulsive, and hyper.”
To test the “All” part of the theory: “ADHD symptoms
will continue for some kids even after sugar is removed
from the diet.”

12. Danger when testing hypotheses:
theories can bias our observations
BIAS: We might select only
the data, or the
interpretations of the
data, that support what
we already believe. There
are safeguards against
this:
Operational definitions
Guide for making useful
observations:
How can we measure
“ADHD symptoms” in the
previous example in
observable terms?
 Impulsivity = # of
times/hour calling
out without raising
hand.
 Hyperactivity = # of
times/hour out of
seat
 Inattention = #
minutes
continuously on task
before becoming
distracted
Operational definition - description of
what actions and operations will be used to
measure the dependent variables and
manipulate the independent variables.

13. The next/final step in the
scientific method:
Replication
You could introduce a small change in the study, e.g.
trying the ADHD/sugar test on college students instead
of elementary students.
Replicating research
means trying the methods
of a study again, but with
different participants or
situations, to see if the
same results happen.

14. Research Process: an example

15. Now that we’ve covered this
We can move on to this
Tophat Question

16. Research goal and strategy:
Description
Strategies for gathering
this information:
Case Study:
observing and
gathering information
to compile an in-depth
study of one individual
Naturalistic
Observation:
gathering data about
behavior; watching but
not intervening
Surveys and
Interviews: having
other people report on
their own attitudes and
behavior
Descriptive
research is a
systematic,
objective
observation of
people.
The goal is to
provide a
clear, accurate
picture of
people’s
behaviors,
thoughts, and
attributes.

17. Case Study
 Examining one individual in
depth
 Benefit: can be a source of
ideas about human nature in
general
 Example: cases of brain
damage have suggested the
function of different parts
of the brain (e.g. Phineas
Gage)
 Danger: overgeneralization
from one example

18.  Observing “natural”
behavior means just
watching (and taking
notes), and not trying
to change anything.
 This method can be
used to study more
than one individual,
and to find truths
that apply to a
broader population.
Naturalistic Observation

19. The Survey
 Definition: A method of
gathering information
about many people’s
thoughts or behaviors
through self-report rather
than observation.
 Keys to getting useful
information:
 Be careful about the
wording of questions
 Only question
randomly sampled
people
Wording
effects
the results you
get from a
survey can be
changed by your
word selection.
Example:
Q: Do you
have
motivation to
study hard for
this course?
Q: Do you feel
a desire to
study hard for
this course?

20. LONGITUDINAL AND CROSS-SECTIONAL
RESEARCH
Figure 2.11 Longitudinal research like the CPS-3 help us to better understand how smoking is associated with
cancer and other diseases. (credit: CDC/Debora Cartagena)
Cross-Sectional Research – Compares multiple segments of a population at a
single time (such as different age groups).
Longitudinal - Studies in which the same group of individuals is surveyed or
measured repeatedly over an extended period of time.
Researchers often expect some participants to drop out, particularly in this type of
study and therefore often initially recruit a lot of participants.
Attrition - reduction in number of research participants as some drop out of the study
over time.

21. Correlation
General Definition: an
observation that two
traits or attributes are
related to each other
(thus, they are “co”-
related)
Scientific definition: a
measure of how closely
two factors vary
together, or how well
you can predict a change
in one from observing a
change in the other
In a case study: The
fewer hours the boy
was allowed to sleep,
the more episodes of
aggression he
displayed.
A possible result of
many descriptive
studies:
discovering a
correlation
In a naturalistic
observation:
Children in a
classroom who were
dressed in heavier
clothes were more
likely to fall asleep
than those wearing
lighter clothes.
In a survey: The
greater the number
of Facebook friends,
the less time was
spent studying.

22. Correlation Coefficient
• The correlation coefficient is a number representing how closely and
in what way two variables correlate (change together).
• The direction of the correlation can be positive (direct relationship;
both variables increase together) or negative (inverse relationship:
as one increases, the other decreases).
• The strength of the relationship, how tightly, predictably they vary
together, is measured in a number that varies from 0.00 to +/- 1.00.
Close to
+1.0
(strong negative
correlation)
(no relationship,
no correlation)
Guess the Correlation Coefficients
(strong positive
correlation)
Height vs. shoe
size
Years in school
vs. years in jail
Height vs.
intelligence
Close to
0.0
Close to
-1.0

23. If we find a correlation,
what conclusions can
we draw from it?
Let’s say we find the following result:
there is a positive correlation between
two variables,
ice cream sales, and
rates of violent crime
How do we explain this?

24. Correlation is not Causation!
“People who floss
more regularly have
less risk of heart
disease.”
“People with bigger
feet tend to be
taller.”
If this data is from a
survey, can we
conclude that
flossing might
prevent heart
disease? Or that
people with heart-
healthy habits also
floss regularly?
Does that mean
having bigger feet
causes height?

25. If self-esteem correlates with
depression,
there are still numerous possible
causal links:
Tophat Question

26. So how do we find out about
causation? By experimentation
 Testing the
theory that
ADHD = sugar:
removing sugar
from the diet of
children with
ADHD to see if it
makes a
difference
 The
depression/self-
esteem
example: trying
interventions that
improve self-
esteem to see if
they cause a
reduction in
Experimentation
: manipulating
one factor in a
situation to
determine its
effect

27. Random Sampling
• If you want to find out something
about men, you can’t interview
every single man on earth.
• Sampling saves time. You can find
the ratio of colors in this jar by
making sure they are well mixed
(randomized) and then taking a
sample.
population sample
Random sampling is a
technique for making
sure that every individual
in a population has an
equal chance of being in
your sample.
“Random” means
that your
selection of
participants is
driven only by
chance, not by
any characteristic.

28. The Control Group
•If we manipulate a variable in an experimental group
of people, and then we see an effect, how do we know
the change wouldn’t have happened anyway?
•We solve this problem by comparing this group to a
control group, a group that is the same in every way
except the one variable we are changing.
Example: two groups of children have ADHD, but
only one group stops eating refined sugar.
By using random
assignment:
randomly selecting
some study
participants to be
assigned to the
control group or the
experimental group.
How do make
sure the control
group is really
identical in every
way to the
experimental
group?

29. Placebo effect
How do we make sure that the
experimental group doesn’t
experience an effect because they
expect to experience it?
How can we make sure both
groups expect to get better, but
only one gets the real intervention
being studied?
Placebo effect:
experimental effects
that are caused by
expectations about
the intervention
Working with the
placebo effect:
Control groups may
be given a placebo
– an inactive
substance or other
fake treatment in
place of the
experimental
treatment.
The control group is
ideally “blind” to
whether they are
getting real or fake
treatment.
Many studies are
double-blind –
neither participants
nor research staff
knows which
participants are in
the experimental or
control groups.

30. The variable we are able to manipulate
independently of what the other variables are
doing is called the independent variable (IV).
• If we test the ADHD/sugar hypothesis:
• Sugar = Cause = Independent Variable
• ADHD = Effect = Dependent Variable
The variable we expect to experience a change
which depends on the manipulation we’re doing is
called the dependent variable (DV).
• Did more hyper kids get to choose to be in the sugar group?
Then their preference for sugar would be a confounding
variable. (preventing this problem: random assignment).
The other variables that might have an effect on the
dependent variable are confounding variables.
Naming the variables

31. To clarify two similar-sounding
terms…
First you sample,
then you sort
(assign)
Random
assignment of
participants to
control or
experimental
groups is how
you control all
variables except
the one you’re
manipulating.
Random
sampling is how
you get a pool of
research
participants that
represents the
population
you’re trying to
learn about.

32. An experiment is a type of
research in which the
researcher carefully
manipulates a limited number
of factors (IVs) and measures
the impact on other factors
(DVs).
*in psychology, you
would be looking at
the effect of the
experimental change
(IV) on a behavior or
mental process (DV).
Filling in our definition of experimentation

33. Correlation vs. causation:
the breastfeeding/intelligence
question
• Studies have found that children
who were breastfed score higher
on intelligence tests, on average,
than those who were bottle-fed.
• Can we conclude that breast
feeding CAUSES higher
intelligence?
• Not necessarily. There is at least
one confounding variable: genes.
The intelligence test scores of the
mothers might be higher in those
who choose breastfeeding.
• So how do we deal with this
confounding variable? Hint:
experiment.

34. Ruling out confounding
variables:
experiment with random
assignment
An actual study in the text: women were randomly selected to
be in a group in which breastfeeding was promoted
+6 points

35. Drawing conclusions from data:
are the results useful?
After finding a pattern
in our data that shows
a difference between
one group and another,
we can ask more
questions.
Is the difference
reliable: can we use
this result to generalize
or to predict the future
behavior of the broader
population?
Is the difference
significant: could the
result have been caused
by random/ chance
variation between the
groups?
How to achieve reliability:
Nonbiased sampling: Make sure the
sample that you studied is a good
representation of the population you are
trying to learn about.
Consistency: Check that the data
(responses, observations) is not too widely
varied to show a clear pattern.
Many data points: Don’t try to generalize
from just a few cases, instances, or
responses.
When have you found statistically
significant difference (e.g. between
experimental and control groups)?
When your data is reliable AND
When the difference between the groups
is large (e.g. the data’s distribution curves do
not overlap too much).
Tophat Question

36. Photo Credits
• Slide 3: © Bettmann/ CORBIS
• Slide 6: Mary Evans Picture Library / Alamy
• Slide 7: Wellesley College Archives
• Slide 8: Center for the History of Psychology Archives of the History of American
Psychology, The University of Akron
• Slide 10:
• © Underwood & Underwood/ CORBIS
• Bachrach/ Getty Images
• Slide 11: Bettmann/ CORBIS
• Slide 12:
• Bettmann/ CORBIS
• Time & Life Pictures/Getty Images
• Slide 32: AP Photo/ Alan Diaz
• Slide 49: AP Photo/Erik S. Lesser
• Slide 63: Lane Oatey /Getty Images
• Slide 64: Michael Wertz