Chapter 1: Thinking Critically With Psychological Science
The Need for Psychological Science
● Mere repetition of statements will make them easier to remember
○ Makes them more true-seeming
○ Misconceptions can overwhelm hard truths
● 3 Roadblocks to Critical Thinking:
○ Hindsight bias
■ The tendency to believe, after learning an outcome, that one would
have foreseen it
■ AKA “I-knew-it-all-along” phenomenon
○ Overconfidence
■ Humans tend to think that they know more than they actually do
■ They tend to be more confident than correct
○ Perceiving patterns in random events
■ For most, an unpredictable world is unsettling
■ Built-in eagerness to make sense of the world
■ Searching for patterns in random data
The Scientific Method
● Constructing theories
○ Theories explain behaviors or events by offering ideas that organize
observations
○ Theory: an explanation using an integrated set of principles that organizes
observations and predicts behaviors and events
○ Good theories produce testable predictions, AKA hypothesis
○ Hypothesis: a testable prediction, often implied by a theory
○ Psychologists report research with precise operational definitions in order
to avoid bias and allow for accurate replication by others
○ Operational definition: a carefully-worded statement of the exact
procedures (operations) used in a research study
○ Replication: repeating the essence of a research study, usually with
different participants in different situations, to see whether the basic
finding can be reproduced
● Description
○ Case Studies (in-depth analyses of individuals)
■ Examines one individual or group in-depth in hopes of revealing
things true of us all
● Brain damage
, ● Children’s minds
● Animal intelligence
■ Case studies involve only one individual or group, so we can’t know
for sure whether the principles observed would apply to a larger
population
○ Naturalistic Observation
■ A descriptive technique of observing and recording behavior in
naturally-occurring situations without trying to manipulate and
control the situation
● Chimpanzees
● Baboons
○ Surveys
■ A descriptive technique for obtaining the self-reported attitudes or
behaviors of a particular group
■ Wording Effects
● Even subtle changes in wording of questions can have major
effects
○ “Gun safety” vs. “gun control”
■ Random Sampling
● Used to avoid bias
● A sample that fairly represents a population because each
member has an equal chance of inclusion
● Correlation
○ A measure of the extent to which two factors vary together, and thus of
how well either factor predicts the other
○ Correlation coefficient: a statistical index of the relationship between two
things
■ Ranges from -1.00 to +1.00
○ Scatterplot: a graphed cluster of dots, each of which represents the values
of two variables
■ Slope suggests direction of the relationship between two variables
■ Amount of scatter suggests strength of correlation
○ Correlation is negative if two sets of scores inversely relate
■ One set travels up, one travels down
● Illusory Correlation and Regression Toward the Mean
○ Illusory Correlation: perceiving a relationship where none exists, or
perceiving a stranger-than-actual relationship
■ Feeds an illusion of control
, ○ Regression toward the mean: tendency for extreme or unusual events to
regress toward the average
● Experimentation
○ Enables researchers to isolate effects of one or more factors by:
■ Manipulating factors of interest
■ Holding constant other factors
○ Double-blind procedure: an experimental procedure in which both the
research participants and research staff are ignorant about whether
participants have received treatment or a placebo
○ Independent variable: the factor that is manipulated; variable whose effect
is studied
○ Confounding variable: factor other than the factor being studied that might
influence a study’s results
○ Dependent variable: the outcome that is measured; variable that changes
when independent variable is manipulated
● Research Design
Method Purpose Conducted by Weaknesses
Descriptive Observe and Case studies, No control of
record behavior observations, variables; single
surveys cases may be
misleading
Correlational Detect Collect data on Cannot specify
naturally-occurrin two or more cause and effect
g relationships; variables; no
assess how well manipulation
one variable
predicts another
Experimental To explore cause Manipulate one or Results may not
and effect more factors apply to other
contexts; not
always ethical
● Predicting Everyday Behavior
○ Psychologists apply laboratory research to actual events through
theoretical principles that have been refined through many experiments
● Protecting Research Participants
○ Animals
, ■ “We cannot defend our scientific work with animals on the basis of
the similarities between them and ourselves and then defend it
morally on the basis of differences.” -Roger Ulrich
■ Humans raise and slaughter 56 billion animals a year
○ Humans
■ Some experiments will not work if participants know everything
beforehand
■ Ethics codes of APA and Britain’s BPS:
● Obtain potential participants’ informed consent
● Protect participants from greater-than-usual harm and
discomfort
● Keep information about participants confidential
● Fully debrief participants afterwards
● Values
○ People have varying values and wordings
Statistical Reasoning in Everyday Life
● Statistics are tools that help us see and interpret what the unaided eye might
miss
● Doubt big, round, undocumented numbers
● Measures of Central Tendency:
○ Mode: most frequently-occurring score(s) in a distribution
○ Mean: arithmetic average, obtained by adding scores and then dividing by
the number of scores
○ Median: middle score in a distribution
● Measures of Variation
○ Range: difference between highest and lowest scores in a distribution
○ Standard deviation: computed measure of how much scores vary around
the mean score
○ Normal curve (normal distribution): a symmetrical, bell-shaped curve that
describes the distribution of many types of data; most scores fall near the
mean and fewer near the extremes
● When is an observed difference reliable?
○ Representative samples are better than biased samples
○ Less-variable observations are more reliable than those that are more
variable
○ More cases are better than fewer
***Generalizations based on a few unrepresentative cases are unreliable
● When is an observed difference significant?