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Thinking Critically With
Psychological Science
Psychological Science
1. How can we differentiate between
uniformed opinions and examined
2. The science of psychology helps make
these examined conclusions, which leads
to our understanding of how people feel,
think, and act as they do!
Thinking Critically with Psychological
The Need for Psychological
 The limits of Intuition and
Common Sense
 The Scientific Attitude
 The Scientific Method
Thinking Critically …
 The Case Study
 The Survey
 Naturalistic Observation
Thinking Critically …
 Correlation and Causation
 Illusory Correlation
 Perceiving Order in Random
Thinking Critically …
 Exploring Cause and Effect
 Evaluating Therapies
 Independent and Dependent
Thinking Critically …
Statistical Reasoning
 Describing Data
 Making Inferences
FAQs About Psychology
What About Intuition & Common
Many people believe that intuition and common
sense are enough to bring forth answers regarding
human nature.
Intuition and common sense may aid queries,
but they are not free of error.
Limits of Intuition
Personal interviewers may
rely too much on their “gut
feelings” when meeting
with job applicants.
Taxi/ Getty Images
• 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!!!)
Sometimes we think we
know more than we
actually know.
How long do you think it
would take to unscramble
these anagrams?
People said it would take
about 10 seconds, yet on
average they took about 3
minutes (Goranson, 1978).
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).
Critical Thinking
Courtesy of the James Randi Education Foundation
Critical thinking does
not accept arguments
and conclusions blindly.
It examines
assumptions, discerns
hidden values,
evaluates evidence and
assesses conclusions.
The Amazing Randi
Scientific Method
Psychologists, like all scientists, use the
scientific method to construct theories that
organize, summarize and simplify
How Do Psychologists Ask &
Answer Questions?
Psychologists, like all scientists, use the
scientific method to construct theories that
organize, summarize and simplify
A theory is an explanation that integrates
principles and organizes and predicts
behavior or events.
For example, low self-esteem contributes to
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.
Research Observations
Research would require us to administer
tests of self-esteem and depression.
Individuals who score low on a self-esteem
test and high on a depression test would
confirm our hypothesis.
Research Process
Case Studies
• A detailed picture of
one or a few
• Tells us a great
story…but is just
• Does not even give
us correlation data.
The ideal case study is John and
Kate. Really interesting, but what
does it tell us about families in
Survey Method
•Most common type of
study in psychology
•Measures correlation
•Cheap and fast
•Need a good random
•Low-response rate
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.
• Identify the
population you want
to study.
• The sample must be
representative of
the population you
want to study.
• Stratified Sampling
Naturalistic Observation
• Watch subjects in
their natural
• Do not manipulate the
• The good is that there
is no Hawthorne
• The bad is that we
can never really show
cause and effect.
Correlational Method
• Correlation
expresses a
relationship between
two variable.
• Does not show
As more ice cream is eaten,
more people are murdered.
Does ice cream cause murder, or murder cause people to eat ice cream?
Types of Correlation
Positive Correlation
• The variables go in
the SAME direction.
Negative Correlation
• The variables go in
opposite directions.
Studying and
grades hopefully
has a positive
Heroin use and
grades probably has
a negative
Correlation Coefficient
• A number that
measures the
strength of a
• Range is from -1 to +1
• The relationship gets
weaker the closer you
get to zero.
Which is a stronger
• -.13 or +.38
• -.72 or +.59
• -.91 or +.04
Perfect positive
correlation (+1.00)
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.
Perfect negative
correlation (-1.00)
No relationship (0.00)
The Scatterplot on the left shows a negative correlation,
while the one on the right shows no relationship between
the two variables.
Data showing height and temperament in people.
The Scatterplot below shows the relationship
between height and temperament in people. There
is a moderate positive correlation of +0.63.
As the graph below (taken from the Church of the Flying Spaghetti Monster website)
shows, two things have happened since the early 19th-century: one is that the
number of pirates has declined, the other is that global average temperatures have
If correlation implied causation, we would be able to infer a connection between
these two events. It is not the case, however, that global warming is an effect of the
decline in piracy. Neither is the decline in piracy the result of increasing
temperatures. Mere correlation does not imply a causal connection.
Correlation = not Causation
Real-World Example
Nestle, the makers of the breakfast cereal Shredded Wheat, once ran an
advertising campaign in which the key phrase was this:
“People who eat Shredded Wheat tend to have healthy hearts.”
This is very carefully phrased. It does not explicitly state that there is any
causal connection between eating Shredded Wheat and having a healthy
heart, but it invites viewers of the advertisements to make the connection;
the implication is there. Whether or not there is any such connection, the
mere fact that the two things are correlated does not prove that there is
such a connection.
Correlation and Causation
Correlation does not mean causation!
Illusory Correlation
The perception of a relationship where no relationship
actually exists. Parents conceive children after adoption.
Do not conceive
Do not Disconfirming
Michael Newman Jr./ Photo Edit
Order in Random Events
Given random data, we look for order and
meaningful patterns.
Your chances of being dealt either of these hands is
precisely the same: 1 in 2,598,960.
Order in Random Events
Given large numbers of random outcomes, a few
are likely to express order.
Jerry Telfer/ San Francisco Chronicle
Angelo and Maria Gallina won two
California lottery games on the same day.
Exploring Cause and Effect
Like other sciences, experimentation is the
backbone of psychological research. Experiments
isolate causes and their effects.
Exploring Cause & Effect
Many factors influence our behavior. Experiments
(1) manipulate factors that interest us, while other
factors are kept under (2) control.
Effects generated by manipulated factors isolate
cause and effect relationships.
Experimental Method
• Looking to prove
causal relationships.
• Cause = Effect
• Laboratory v. Field
Smoking causes health issues.
Experimental vs. Control
• Experimental Group
– The group exposed to manipulation of the
independent variable
– E.g. receives the DROW-Z’s
• Control Group
– Group NOT exposed to manipulation of the
independent variable; used for COMPARISON
– E.g. does NOT receive DROW-Z’s
– May instead receive a PLACEBO
• Random assignment to groups
– All subjects have an equal chance of being in either
the control group or experimental group!
Operational Definitions, Etc.
• Operational Definitions
– What are we measuring and how?
– How are we defining VARIABLES (IV/DV)?
– Allows experiment to be replicated by others
– E.g. what is a “better” night’s sleep?
• Sample Size: the bigger the better!
• What is the difference between groups?
• Replication?
Evaluating Therapies
Double-blind Procedure
In evaluating drug therapies, patients and
experimenter’s assistants should remain
unaware of which patients had the real
treatment and which patients had the placebo
Random Assignment
• Once you have a
random sample,
randomly assigning
them into two groups
helps control for
confounding variables.
• Experimental Group v.
Control Group.
• Group Matching
Independent Variable
• Whatever is being
manipulated in the
• Hopefully the
independent variable
brings about change.
If there is a drug in an
experiment, the
drug is almost always
the independent
Dependent Variable
• Whatever is being
measured in the
• It is dependent on the
independent variable.
The dependent variable
would be the effect
of the drug.
Operational Definitions
• Explain what you mean
in your hypothesis.
• How will the variables
be measured in “real
life” terms.
• How you
operationalize the
variables will tell us if
the study is valid and
Let’s say your hypothesis
is that chocolate causes
violent behavior.
• What do you mean by
• What do you mean by
violent behavior?
Beware of
Confounding Variables
If I wanted to prove that
smoking causes heart
issues, what are some
confounding variables?
• The object of an
experiment is to prove
that A causes B.
• A confounding variable
is anything that could
cause change in B, that
is not A.
Lifestyle and family
history may also
effect the heart.
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.
Experimenter Bias
• Another confounding
• Not a conscious act.
• use Double-Blind
Procedure to
counter this
• Recording the
results from our
• Must use a common
language so we all
know what we are
talking about.
Descriptive Statistics
• Just describes sets
of data.
• You might create a
frequency distribution.
• Frequency polygons
or histograms.
Measures of Central Tendency
Mode: The most frequently occurring score
in a distribution.
Mean: The arithmetic average of scores in a
distribution obtained by adding the
scores and then dividing by the number
of scores that were added together.
Median: The middle score in a rank-ordered
Central Tendency
• Mean, Median and Mode.
• Watch out for extreme scores or outliers.
Let’s look at the salaries of the
employees at Dunder Mifflen Paper
in Scranton:
$25,000- Kevin
$25,000- Angela
$100,000- Andy
$100,000- Dwight
$200,000- Jim
$300,000- Michael
The median salary looks good at
The mean salary also looks good at
about $110,000.
But the mode salary is only $25,000.
Maybe not the best place to work.
Normal Distribution
In a normal
distribution, the
mean, median of
the central
tendency are
Sample Data Set:
1, 1, 2, 2, 2, 3, 3, 3,
3, 4, 4, 4, 5, 5
Measures of Central Tendency
A Skewed Distribution
• Outliers skew
• If group has one high
score, the curve has a
positive skew
(contains more low
• If a group has a low
outlier, the curve has
a negative skew
(contains more high
Measures of Variation
Range: The difference between the highest and
lowest scores in a distribution.
Standard Deviation: A computed measure of
how much scores vary around the mean.
Descriptive Statistics:
Measures of Variation
Range – the difference between the highest and lowest score
in a distribution
– What does it tell you?
– What DOESN’T it tell you?
Standard Deviation – how much do scores vary from the mean
in a distribution? (see table 1.4 in text p. 36)
1. Calculate mean
2. Calculate each scores deviates from the mean
3. Square that difference
4. Add the sum of the squares
5. Divide by the number of scores in the distribution
6. Take square root of this
7. The number is equal to the value of ONE standard deviation
Standard Deviation
Descriptive Statistics:
Measures of Variation
• So what?
– In a normal curve, this number reveals the percentage of
scores that falls within a particular range
– 68% fall within one standard deviation from the mean
– 96% fall within two standard deviations from the mean
– 99% fall within three standard deviations from the mean
What must the
standard deviation
be for this
distribution of IQ
Below is a comparison of different research
Illusion of Control
That chance events are subject to personal control is an
illusion of control fed by:
1. Illusory Correlation: the perception of a relationship
where no relationship actually exists.
2. Regression Toward the Mean: the tendency for
extremes of unusual scores or events to regress
toward the average.
Making Inferences
A statistical statement of how frequently an
obtained result occurred by experimental
manipulation or by chance.
Making Inferences
When is an Observed Difference Reliable?
1. Representative samples are better than biased
2. The less variation in the data, the more reliable
(if variability is high in a distribution, the mean
becomes less meaningful)
3. More cases are better than fewer cases. (ask 2
friends how they like the class vs. asking 25)
Making Inferences
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. It is
probably not due to chance variation.
For psychologists this difference is measured
through alpha level set at 5 percent. If possibility
of chance is above 5%, then study loses value.
Significant Difference?
• What is the difference between the experiences of the
control and the experimental groups?
• What is the chance that the difference happened due to
• If it IS a significant difference, how important is that
difference (e.g. difference between IQ scores of first- and
later-born children is significant, but due to its very small
value, it is not important.
Normal Distribution
Statistical Significance
• p = .05
• p = The probability that
the results of the
experiment were due
to chance variations in
the sample groups
• Findings which have
a p value above 5%
don’t find those
results valuable.
• p = .01 is more
statistically significant
than p = .03
Frequently Asked Questions About
Q1. Can laboratory experiments illuminate
everyday life?
Ans: Artificial laboratory conditions are created to
study behavior in simplistic terms. The goal is to
find underlying principles that govern behavior.
Q2. Does behavior depend on one’s culture and gender?
Ans: Even when specific attitudes and behaviors vary across
cultures, as they often do, the underlying processes are much
the same. Biology determines our sex, and culture further
bends the genders. However, in many ways woman and
man are similarly human.
Ami Vitale/ Getty Images
Q3. Why do psychologists study animals, and is it ethical
to experiment on animals?
Ans: Studying animals gives us the understanding of many
behaviors that may have common biology across animals
and humans. From animal studies, we have gained insights
to devastating and fatal diseases. All researchers who deal
with animal research are required to follow ethical
guidelines in caring for these animals.
D. Shapiro, © Wildlife Conservation Society
Q4. Is it ethical to experiment on people?
Ans: Yes. Experiments that do not involve any
kind of physical or psychological harm beyond
normal levels encountered in daily life may be
carried out.
Q5. Is psychology free of value judgments?
Ans: No. Psychology emerges from people who
subscribe to a set of values and judgments.
© Roger Shepard
Q6. Is psychology potentially dangerous?
Ans: It can be, but is not when practiced
responsibly. The purpose of psychology is to help
humanity with problems such as war, hunger,
prejudice, crime, family dysfunction, etc.