UW Psychology
1000/6
L. Ron Hubbard
What is Science?
What is meant by
"scientific" Psychology?
I believe astrology might have
at least some validity.
A=
B=
C=
D=
Mostly agree
Somewhat agree
Somewhat disagree
Mostly disagree
Beliefs
Do you believe in astrology?
Beliefs are wholly personal
Belief vs claims of fact
Scientific belief vs Religious belief
Pan-critical rationalism
What is Science?
Science= Rules of dispute resolution
Scientists agreeing, in advance, on a way for
peacefully resolving disputes
2 ways to resolve disputes:
 Non-peacefully
 Peacefully
1) Authority
2) Agreement on rules for
resolving disputes
Political Claims:
Dispute resolution
mechanism?
voting
Knowledge claims:
Dispute resolution
mechanism?
science
At the heart of science is an essential
tension... an openness to new ideas,
no matter how bizarre or
counterintuitive they may be, and the
most ruthless skeptical scrutiny of
all ideas, old and new.
Carl Sagan
Context of Discovery
(free, open)
Context of Verification
(hardheaded, skeptical)
Fact
Observation to be explained
Theory
Coherent principles that “POG”
predict, organize, generate
hypotheses.
Hypothesis
Specific prediction that is testable.
Characteristics of Science
Verifiable
empirical, replicable
Public
free exchange of information (no
secrets)
Parsimonious
Occam's Razor
Cumulative
knowledge changes & tends to grow
Advantages of Science
reliable (trustworthy)
valid (rigorously verified)
efficient
freedom promoting
spirit of science ---> liberaldemocratic social values:
liberty, openness, tolerance,
equality,
When our natural thinking style fails:
Overconfidence
Hindsight bias:
error:
“I knew it all
sure I am
along.”
The coincidence “I am
correct.”
error, or
mistakenly
perceiving order
in random
events:
“The dice must
be fixed because
you rolled three
sixes in a row.”
Why do we make these errors and
overuse our intuition?
From an evolutionary perspective:
Hindsight bias
might be an
offshoot of our
useful habit of
analyzing an
event and trying
to figure out
why it occurred.
Perceiving
order helps us
make
predictions; we
just need to
test these and
not overdo it.
Overconfidence
error
might help us
lead other
people;
certainty builds
confidence in
followers more
than accuracy
does.
Sometimes our
intuition gives the
right answer, which
makes us trust it
even more.
Making our ideas more accurate by
being scientific
What did “Amazing Randi” do
about the claim of seeing
auras? He developed a
testable prediction, which
would support the theory if it
succeeded.
Which it did not.
The aura-readers were
unable to locate the aura
around Randi’s body without
seeing Randi’s body itself, so
their claim was not
supported.
Therapeutic Touch (TT)
• Emily Rosa
• Youngest to publish in
medical journal (age 9)
• Science Fair project
• “Human Energy Field” (HEF)
• TT therapists tested.
• Place hands through holes.
• Emily holds hand over one
of them. 10 tries. 4.4/10
Disadvantages of Science
Often a slow process
Hard to understand
technical jargon
complex
sophisticated (long learning curve)
answers often ambiguous
Are some questions outside science?
“Will my mind exist after I die?”
Goals of Science
Measurement and description
quantification… -->
mathematics
Understanding and prediction
precise description
general laws
boundary conditions
prediction
Lab vs Field Research
Laboratory Research
 influences controlled
 observations systematic
Field Research
 context more natural
("high ecological validity")
Measurement in Psychology
1. Self-Reports
2. Behavioral Observation
3. Physiological recordings
4. Archival Records
Research Methods
I. Correlational
 describe, classify
 find associations
 NOT able to determine causes
II. Experimental
 controls extraneous variables
 can now test if variable causes outcome of
interest
Descriptive/Correlational Methods
 Case studies
• in-depth observations of individual
persons.
 Surveys
• interviewing or giving questionnaires to a
large number of people.
 Naturalistic observations
• observation of behavior as it occurs
naturally in real-world settings
The "Correlation" Coefficient
Correlation e.g. r = .42
–Numerical index of association.
–Ranges -1 to 1
–varies in: magnitude
–varies in: direction (+, -)
–-1.0 -.76 ...0… +.42
+1.0
Which correlation is the strongest?
A)
B)
C)
D)
.32
.28
-.20
-.38
r = +1.0
r = -1.0
r = .00
r = -.60
r = -.30
What is the correlation between
height and weight?
A.
B.
C.
D.
-.60
+.30
+.60
-.30
What is the correlation between
exam1 and exam2?
A.
B.
C.
D.
-.20
+.40
+.70
-.50
What is the correlation between
depression and self-esteem?
A.
B.
C.
D.
-.10
+.40
+.70
-.50
What is the correlation between
belief in God and empathy?
A.
B.
C.
D.
.00
+.15
+.50
-.30
Religious vs. Spiritual . . .
Religious vs. Spiritual
What is the correlation between
belief in God and empathy?
A.
B.
C.
D.
.00
+.15
+.50
-.30
What is the correlation between
weight and income?
A.
B.
C.
D.
-.70
+.20
+.50
-.40
Weight correlates +.20 with income!
Why ?
Weight
Income ?
Income
Weight ?
Weight
Income
age
Experimental Methods
1. Wiggle one thing.
2. Control everything else.
3. Carefully observe the outcome
Experimental Methods

Advantages
control
causal conclusions

Disadvantages
artificial
often can't use
Basic Design of Experiments
 Variables
Things that can vary (vary – able)
 Participants
Intro psyc students
Human guinea pigs
Actual guinea pigs
Variables
 Independent variable
the thing you wiggle
 Dependent variable
the resulting effect
your outcome measurement
Participants
• Representative sampling
• Random assignment to conditions
• Blind to hypotheses and conditions
What is a “double-blind” experiment?
What is a double-blind experiment?
A. Research using 1-way mirror
B. Random assignment of subjects
C. Participants unaware which condition
they are in.
D. Neither researcher nor participant
knows which condition participant
was in.
Schacter et al. (1962)
Hypothesis: Anxiety increases the
need for affiliation
I.V.
Anxious vs Control condition
D.V.
preference for room with people
in it versus empty room.
Schacter
et al. (1962)
RESULTS
Lang et al. (1975)
 Alcohol and aggression
Due to alcohol?
Due to role expectations?
Design
• Vary alcohol (half get tonic)
• Vary beliefs (half misled)
• Vary provocation (half provoked)
Measure how aggressive.
How many groups were compared?
A. 3
B. 6
C. 8
2x2x2=
8 groups
Provoked
Expected Expected
Alcohol
Tonic
Not Provoked
Expected
Alcohol
Expected
Tonic
Copyright © Allyn and Bacon
Begue et al. (2013)
Ethics
Considerations in
Human Research
Ethics
Considerations in
Animal Research
Begue et al. (2013)
 Study 1: BAR
Yes, more drinks, more attactive
they rated themselves.
 Study 2: LAB
• Drank alcohol vs non-alcohol
• Told truth about drink vs misled
• Gave a speech (videotaped)
22 judges rated the videotaped
speeches.
Begue et al. (2013)
 Study 2: LAB
• Participants also rated their own
performance.
RESULT?
• Alcohol misled participants rated
themselves highest in performance.
Tonic misled < Alcohol misled
2013 IgNobel Prize
IgNobel Prize:
Weirdest Research of the Year
Ignoble
“of low character”
“not noble”
Ethics
 Human Research
 Animal Research
Protecting Human Participants
1) Informed Consent
enough information to let them
decide freely
2) Freedom to withdraw at any time
3) Minimize discomfort
4) Keep data confidential
5) If deception used, debriefing required.
Animal Research Ethics
Animal Welfare
• humane treatment are universally
supported
• Allegations of mistreatment in
laboratories are rarely supported
Animal Rights
• There is no consensus over whether
animals have similar rights as humans
Q: Should level of animal rights
depend on level of psychological
capacities of the animal?
A. Yes
B. No
Which do you feel more emotional
connection for?
From data to insight: statistics
 We’ve done our
research and
gathered data.
Now what?
 We can use
statistics, which are
tools for organizing,
presenting,
analyzing, and
interpreting data.
The Need for Statistical Reasoning
 A first glance at our observations
might give a misleading picture.
Example: Many people have a
misleading picture of what income
distribution in America is ideal,
actual, or even possible.
 Value of statistics:
1. to present a more accurate
picture of our data (e.g. the
scatterplot) than we would see
otherwise.
2. to help us reach valid
conclusions from our data;
statistics are a crucial critical
thinking tool.
Tools for Describing Data
The bar graph is one simple display method
but even this tool can be manipulated.
Our
brand of
truck is
better!
Our brand
of truck is
not so
different…
Why is there a difference in the apparent result?
Measures of central tendency
Are you looking for just ONE NUMBER to describe
a population’s income, height, or age?
Options:
Mode
•the most
common
level/number/
score
Mean
Median
(arithmetic
“average”)
(middle person’s
score, or 50th
percentile)
•the sum of the
scores, divided by
the number of
scores
•the number/level
that half of
people scored
above and half of
them below
Measures of central tendency
Here is the mode, median, and mean of a
family income distribution. Note that this is a
skewed distribution; a few families greatly
raise the mean score.
Why does this seesaw balance?
Notice these gaps?
A different view, showing why the
seesaw balances:
The income is so high for some families on the
right that just a few families can balance the
income of all the families to the left of the
mean.
Measures of variation:
how spread out are the scores?
 Range: the difference between the highest and
lowest scores in a distribution
 Standard deviation: a calculation of the average
distance of scores from the mean
Small standard deviation
Large standard deviation
Mean
Skewed vs. Normal Distribution
 Income distribution is skewed by the very rich.
 Intelligence test distribution tends to form a
symmetric “bell” shape that is so typical that it is
called the normal curve.
Skewed distribution
Normal
curve
Applying the concepts
Try, with the help of this rough drawing
below, to describe intelligence test scores
at a high school and at a college using the
concepts of range and standard deviation.
Intelligence test
scores at a high
school
Intelligence test
scores at a college
100
Schacter
et al. (1962)
RESULTS