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Transcript
Research Methods
Unit 2
1
Hindsight Bias
Hindsight Bias is the “I-knew-it-all-along”
phenomenon.
After learning the outcome of an event, many
people believe they could have predicted that very
outcome.
2
Overconfidence
We tend to think we know more
than we do.
82% of U.S. drivers consider
themselves to be in the top 30% of
their group in terms of safety
81% of new business owners felt they
had an excellent chance of their
businesses succeeding. When asked
about the success of their peers, the
answer was only 39%. (Now that's
overconfidence!!!)
3
The Barnum Effect
It is the tendency for
people to accept very
general or vague
characterizations of
themselves and take
them to be accurate.
The Scientific Attitude
The scientific attitude is composed of curiosity
(passion for exploration), skepticism (doubting
and questioning) and humility (ability to accept
responsibility when wrong).
5
Scientific Method
Psychologists, like all scientists, use the
scientific method to construct theories that
organize, summarize and simplify
observations.
6
Applied V. Basic Research
• Applied Research
has clear, practical
applications.
• YOU CAN USE IT!!!
• Basic Research
explores questions
that you may be
curious about, but
not intended to be
immediately used.
Studying how
kissing changes
when you get
older is
interesting…but
that’s about it.
Research on therapies for drug addicts has
a clear purpose.
Scientific Method
1. Observe some aspect of the universe.
2. Invent a theory that is consistent
with what you have observed.
3. Use the theory to make predictions.
4. Test those predictions by
experiments or further observations.
5. Modify the theory in the light of your
results.
6. Go to step 3.
8
Theory
A Theory is an explanation that integrates
principles and organizes and predicts
behavior or events.
For example, low self-esteem contributes to
depression.
9
Hypothesis
A Hypothesis is a testable prediction, often
prompted by a theory, to enable us to
accept, reject or revise the theory.
People with low self-esteem are apt to feel
more depressed.
• All hypothesis’s must have operational
definitions & be replicable.
10
Null Hypothesis
• the hypothesis the researcher tries to disprove.
• The researcher never proves or accepts the null
hypothesis, but can only reject it or not reject it
Example:
Hypothesis: Roses exhibit greater rate of growth when planted in
soil rather than compost.
Null Hypothesis: Roses do not exhibit greater rate of growth when
planted in soil rather than compost.
• 2nd example….You might see it written like this:
H1: Gender has an effect on spatial ability
H0: Gender does not have an effect on spatial ability
11
Operational Definitions
• precise statements of the procedures
(operations) used to define the variables
• Example
– Anxiety is a concept that most of us are all too
familiar with. It is an unpleasant feeling that
occurs in certain situations. It can disrupt our
functioning if it is excessive, but it also
motivates behavior. So how do you measure
it? How do you operationally define anxiety?
12
Operational definitions
continued
• Since this is a concept that we have first-hand knowledge of, we
might start the process of operationally defining anxiety by asking
ourselves what it is like. What do we feel? How do we react? How
do others react? What features in other people would suggest to us
that they are anxious?
– Self reported answers
– Physiological arousal (heart beating fast, sweating, shaking, trembling, nervous
stomach, stomach ache, accelerated breathing, rise in temperature, decrease in
temperature, etc…)
 Lets try coming up with a few
 A psychologist wants to know if his new form of
psychotherapy will make people less depressed.
 College athletes are not as smart as regular students.
 The teacher wants to find a way to help make Billy act more
friendly toward the other children
13
Replicate (Replication)
• repeating the essence of a research study,
usually with different participants in
different situations, to see whether the
basic finding extends to other participants
and circumstances
• Doing it again to see if you get the same
results
14
What is going on in this picture?
We cannot say exactly, but we
can describe what we see.
Thus we have…..
Descriptive Research
• Any research that observes and records.
• Does not talk about relationships, it just
describes the situation
15
Types of Descriptive Research
• Case Study Method
• Survey Method
• Naturalistic Observation Method
16
Case Study
A technique in which one person is studied in
depth to reveal underlying behavioral principles.
https://abdullaman.wordpress.com/2011/05/01/five
-landmark-psychology-case-studies-you-shouldknow-about/
17
Clinical Case Study
is a form of case study
in which the therapist
investigates the
problems associated
with a client.
http://behavioralhealth.typepad.com
You cannot apply what
you learn from a case
study to the entire
population.
18
Survey
A technique for ascertaining the self-reported
attitudes, opinions or behaviors of people
usually done by questioning a representative,
random sample of people.
http://www.lynnefeatherstone.org
19
The Survey Method
• Used in both descriptional and
correlational research.
• Use Interview, mail, phone, internet
etc…
• The Good- cheap, anonymous, diverse
population, and easy to get random
sampling (a sampling that represents
your population you want to study).
20
Survey Method: The Bad
• Low Response
Rate
• People Lie or
just
misinterpret
themselves.
• Wording
Effects
How accurate would a survey be
about the frequency of
diarrhea?
21
Wording Effect or Framing
Wording can change the results of a survey.
Q1: Should nude ads be allowed on TV?
Or
Q2: Should nude ads be forbidden on TV?
The second question adds a value judgement
and can sway the way people think
22
Random Sampling
If each member of a
population has an equal
chance of inclusion into a
sample, it is called a
random sample
(unbiased). If the survey
sample is biased, its
results are not valid.
The fastest way to know about the
marble color ratio is to blindly
transfer a few into a smaller jar and
count them.
23
Why do we sample?
• One reason is the avoid the False
Consensus Effect: The tendency to
overestimate the extent to which
others share our beliefs and behaviors.
24
Population
• All the possible people or cases within a specific
group
– Example:
• I want to know what students of at SMHS think about the
food in the cafeteria
– My population is every single student at SMHS
» There is NO way I’m going to be able to get to survey
EVERY student, so I would take a RANDOM
SAMPLE
» I’d pass out surveys during all the lunches to each
student that walked into the cafeteria on a given day.
» Those students that returned the survey are now part
of my sample
25
Naturalistic Observation
• Observing and
recording
behavior in
natural
environment.
• No control- just
an observer.
What are the benefits and detriments of
Naturalistic Observation?
What did Jane Goodall do?
26
Correlational Research
• Detects relationships between variables.
• Does NOT say that one variable causes
another. (Correlation DOES NOT EQUAL
CAUSATION)
Did you know that
there is a relationship
between ice cream
sales and murder
rates. Does that mean
that people who buy
ice cream are
murders? Or that
eating ice cream
causes you to murder
someone?
27
Correlation
When one trait or behavior accompanies
another, we say the two correlate.
Indicates strength
of relationship
(0.00 to 1.00)
Correlation
coefficient
Correlation Coefficient is a
statistical measure of the
relationship between two
variables.
r = + 0.37
Indicates direction
of relationship
(positive or negative)
28
Scatterplots
Line of best fit or regression
line is the smooth line that
reflects the general pattern in
a graph. You can draw a line
through each dot
Scatterplot is a graph
comprised of points
that are generated by
values of two
variables. The slope of
the points depicts the
direction, while the
amount of scatter
depicts the strength of
the relationship.
29
Scatterplots
Negative correlation
As one variable goes
up the other goes
down
You can look at the
correlational coefficient
to see if there is a
negative sign (-) after
the r =
Positive correlation
As one variable goes up the
other goes up or as one goes
down the other goes down
You can look at the
correlational coefficient to
see if there is a positive
30
sign (+) after the r =
Example Scatterplot
The scatterplot below shows the relationship
between height and temperament in people.
r= +0.63
Illusory Correlation
The perception of a relationship where no relationship
actually exists. Parents conceive children after adoption.
Adopt
Confirming
evidence
Disconfirming
evidence
Do not
adopt
Disconfirming
evidence
Confirming
evidence
Michael Newman Jr./ Photo Edit
Conceive
Do not
conceive
32
The Experiment
• Only research method
capable of showing cause
and effect
Experimental Research
• Explores cause and effect relationships.
Eating too many bananas causes
Constipation
34
The
st
1
few steps of an
experiment
• You have your question & your hypothesis
• Pick your population
• You have to randomly sample individuals from
your population
• Your sample must be a representative sample
– a sample that accurately reflects the
characteristics of the population as a whole
35
Stratified sampling
• a process or selecting individuals from a
population in such a way that the subgroups in
the population are represented in the sample,
the population is divided into subpopulations and
random samples are taken of each stratum.
– At SMHS we have a very diverse population
so I would need to make sure each subgroup
is represented in my sample.
Now you have your participants for your
experiment. What do you do next?
36
Random Assignment
• Assigning participants to one of the
condition groups in such a way that all
participants have equal chance of being
chosen.
37
Groups (must be randomly
assigned)
Experimental group
• Group that has the
experiment done on them
• Receives the
Independent variable (IV)
– The variable the
experimenter manipulates
Control Group
• Group that DOES NOT
have the experiment
done on them
• Does NOT receive the
independent variable
38
Variables
• Independent Variable (I.V.): what is
manipulated by experimenter
– The effect of the independent variable is the
focus of the study.
• Dependent Variable (D.V.): What is
MEASURED or influenced by the independent
variable
• Confounding/Extraneous variables
– Other variables that can effect the outcome
of the experiment or study that were not
controlled for or can not be controlled
Example
When examining the effects of breast feeding upon
intelligence
Breast feeding is the independent variable
Intelligence is the dependent variable
Are there other variables that effect intelligence?
Those would be confounding or extraneous
variables
40
Control Measures
• Single-Blind: subjects are unaware of their
assignment group
• Double-Blind: subject and experimenter
unaware of placement
– Best to use to avoid experimenter and
participant bias
More Control Measures
Placebo: inert substance that is in place of IV in
Control Group.
Placebo effect: results caused by expectations
alone; any effect on behavior caused by the
administration of an inert substance or condition
42
Hawthorne Effect
• But even the control
group may
experience changes.
• Just the fact that
you know you are in
an experiment can
cause change.
Whether the lights were brighter or
dimmer, production went up in the
Hawthorne electric plant.
Other Research Method
Ex Post Facto (after the fact)
• Research in which we choose subjects based on a preexisting condition like race or gender
• Not a true independent variable
• No cause and effect
• Often used due to ethical concerns
• Describes differences between groups of participants
that differ naturally
Flaws in Research happen
•
•
•
•
•
Sampling Bias
Overgeneralization
Placebo effect
Hawthorne & Barnum effect
Demand Characteristics
– a subtle cue that makes participants aware of
what the experimenter expects to find or how
participants are expected to behave. Can change
the outcome of an experiment because
participants will often alter their behavior to
conform to the experimenters expectations
• Experimenter Bias
Comparison
Below is a comparison of different research
methods.
46
Evaluating Research
You need to know the STRENGTHS AND
WEAKNESSES of each of the following:
Experiment
Correlation
Surveys
Naturalistic Observation
Case Studies
Descriptive Statistics
• Just describes sets
of data
• You might create a
– frequency distribution
– frequency polygons
– Histogram
Measures of Central Tendency
• Mean – average score
• Mode – most reoccurring score
• Median – middle score
• The mean salary is about $110,000
so I can say the mean salary is
$110,000 (I pay my employees very
well). But is that really the case?
• The median salary looks good at
$100,000.
• But the mode salary is only
$25,000.
Maybe my data shows that my
company is not the best place to
work.
Let’s look at the salaries of the
employees at one company
$25,000- cashier
$25,000- stock room
$25,000- assistant manager
$100,000- manager
$100,000- manager
$200,000- regional manager
$300,000- owner
To calculate the mean: Add up
all the salaries ($775,000) and
divide by the number of people
(7).
To calculate the median, I put
all the scores in order (See
above).
The Normal Curve
50
51
Skewed Distributions
• Negatively Skewed
– When a distribution
includes extreme scores
that are unusually high
• Positively Skewed
– When a distribution
includes extreme scores
that are low
52
Skewed Scores
• Positively skewed
• Negatively skewed
53
Measures of Variation
• Range:
– distance between the highest and lowest scores
• Variance:
– the degree to which a set of values varies from the mean of
the set of values
• Standard Deviation:
– average amount by which the scores in a distribution deviate
around the mean.
• Z-scores:
– tells you how far the raw score is away from the mean in
terms of standard deviation units
Standard Deviation: the
variance of scores
around the mean.
• The higher the
variance or SD, the
more spread out the
distribution is.
• Do scientists want a
big or small SD?
Shaq and Kobe may
both score 30 points
per game (same
mean).
But their SDs are
very different.
Standard Deviation
56
Scores
• A unit that measures
the distance of one
score from the
mean.
• A positive z score
means a number
above the mean.
• A negative z score
means a number
below the mean.
Inferential Statistics
Inferential Statistics
• Interpret data and draw conclusions
• Used to test validity of hypothesis (t-test)
• Determine whether or not findings can be
applied to the larger population from which the
sample was selected
– Making sure the results are not due to sampling error
and chance
Sampling error
• the extent to which a sample differs from the population
58
When is a Difference Significant?
When sample averages are reliable and the
difference between them is relatively large, we say
the difference has statistical significance or is
statistically significant.
For psychologists this difference is measured
through alpha level (ᾁ) set at .05% or 1%
5% (p<.05) or 1% (p<.01) level of significance
59
Statistical Significance
If the results are statistically significant
• The difference is NOT due to Chance
• Meaning the manipulation of the IV created a
change in the DV
• If the results were NOT statistically significant
• then the results WERE due to chance and the
manipulation of the IV did not cause a change in
the DV
60
Ethical Guidelines for Research
• APA • IRB- Institutional
Review Board
• Rules for both
humans and animals.
APA Ethical Guidelines for
Human Research
All research goes before an institution review board (IRB) for approval
Research involving humans must meet the following standards:
1. Coercion-participants cannot be forced in any way to participate in the
study
2. Informed Consent-participants must know that they are involved in
research and give their consent or permission
3. Anonymity/Confidentiality -the identities and actions of participants must
not be revealed in anyway by the researcher
4. Risk -participants cannot be placed at significant mental or physical risk.
DO NO HARM
5. Debriefing -participants must be told of the purpose of the study and
provided with ways to contact the researchers about the results after the
study is complete
Deception-if the participants are deceived in any way about the nature of the study the
participants must be debriefed after the study is over
62
Ethics for Animal Research
• Clear scientific purpose
• Treated & cared for in a
humane way
• Acquire animals legally
• Least amount of
suffering possible…Do
No Harm
• A trained psychologist
must supervise all
research with animals