Transcript Document 7195346

AP Psychology: Chapter 1: Thinking
Critically With Psychological Science
Solve ME
• A man is traveling from work and wants
to go home. He will not go home because
there is another man in a mask waiting
there for him. What does the first man
do for a living?
• The man is a runner at third base and he
is trying to score a run
Solve ME
• A man is found shot to death in a
room with a table, four chairs, and
53 bicycles. Why was he murdered?
• There are 52 Bicycle playing cards in
a normal deck. He was playing with
an extra ace.
• What is critical thinking?
• How does it relate to
psychology and this
course?
Let’s Make A Deal!
• One Volunteer is
Needed for A
chance to win
10,805.53
Zimbabwe
Dollars!!
Let’s Make A Deal Shows Us That:
• Human Intuition is highly limited.
• Critically thinking rarely comes easily to us!
– Critical Thinking: thinking that does not blindly
accept arguments and conclusions
• examines assumptions
• discerns hidden values
• evaluates evidence
• An awareness to our own vulnerability
Lack of Intuition
• Hindsight Bias: tendency to believe,
after learning an outcome, that one
would have foreseen it.
• the “I-knew-it-all-along” phenomenon
Lack Of Intuition
• Overconfidence: we tend to think we
know more than we do.
• We can't always trust our common sense
or intuition we need research
Research Strategies
• Theory
– an explanation using an integrated set of
principles that organizes and predicts observations
– Low self esteem contributes to depression
• Hypothesis
– a testable prediction
– often implied by a theory
– Allows us to test and reject or revise the theory
– People with low self esteem score higher on a
depression scale
Scientific Method
theories
lead to
generate or refine
lead to
research and
observations
hypothesis
How to check our bias
• Operational Definition
– a statement of procedures (operations)
used to define research variables
– You want to be clear enough so that the test and
observations can be replicated
– To give the study more credibility it is
usually done with different subjects in
different situations
– Make sure studies are valid and reliable
Research Strategies
• 1. Descriptive- making observations that
describe behavior
• 2. Correlational- detecting correlations
that help predict behavior
• 3. Experimental-doing studies that help
explain behavior
Research Methods- Descriptive
• Case Study
– an observation technique in which one
person is studied in depth in the hope of
revealing universal principles
– Longitudinal
– Cross Sectional
– Drawbacks of case study: individuals can
be atypical and lead to false findings.
• Anecdotal Stories
Research Methods- Descriptive and
Correlation
• Survey
–technique for ascertaining the selfreported attitudes or behaviors of
people
–usually by questioning a
representative, random sample of
them
Components of Survey
• Population: all the individuals you are
interested in knowing something about.
• Sample: the individuals you actually question.
• Sampling should always be taken randomly from
the population so that it is representative,
meaning each individual in the population had
an equal chance of being selected.
Drawbacks of Surveys
1.) Improper Sampling
2.) Question Wording Can Effect the results of a survey.
Ex: Should the sale of alcohol be banned in school
zones?
Should the government not allow the sale of
alcohol in school zones?
Importance of Proper Sampling
• False Consensus Effect: tendency to
overestimate the extent to which others
share our beliefs and behaviors.
• Overgeneralizing extreme examples can
lead you to false conclusions!
Types of Research-Descriptive
• Naturalistic Observation: observing and
recording behavior in naturally occurring
situations without trying to manipulate
and control the situation
• Drawbacks: hard to identify any type of
causation since there is no controls.
Correlation Research
• Correlation Research: research that
looks at a relationship between two
things. How well does one factor predict
the other?
• Ex: Consumption of Ice Cream and
Drowning.
Types of Correlations
• Positive Correlation: a relationship in which
increases in one variable leads to increases in
the other.
• Ex: Amount of fat burned is positively
correlated with amount of sit-ups completed
• Negative Correlation: a relationship in which
increases in one variable leads to decreases in
the other.
• Ex: As tooth brushing goes up, tooth decay
goes down
Some More Correlation Examples
• Married people tend to have higher measures of
happiness.
• Children who watch high amounts of television are
more aggressive.
• People with low self-esteem are more likely to be
depressed.
What meanings can we make of these examples?
Correlations Continued
• Correlation Coefficient: the statistical measure of
the extent to which two factors vary together and
thus how well either factor predicts the other.
(number that measures strength of the
correlation).
• STRONGEST CORRELATIONS are +1 and –1. +1 is a
perfect positive correlation while –1 is a perfect
negative correlation.
• Correlations are always between –1 and +1. A
correlation of Zero means there is no relationship.
Correlation Scatterplots
Perfect positive
correlation (+1.00)
No relationship (0.00)
Perfect negative
correlation (-1.00)
Indicates direction
of relationship
(positive or negative)
Correlation
coefficient
r = +.37
Indicates strength
of relationship
(0.00 to 1.00)
• R=+.37
• R=-1.00
• R=+.17
• R= -.08
Correlation Measures
• Scatterplot
– a graphed cluster of dots, each of which
represents the values of two variables
– the slope of the points suggests the direction of
the relationship
– the amount of scatter suggests the strength of
the correlation
• little scatter indicates high correlation
– also called a scattergram or scatter diagram
95
Temperament 90
scores 85
80
75
70
65
60
55
50
45
40
35
30
25
Height in inches
Height and Temperament of 20 Men
Height in
Subject Inches Temperament
1
2
3
4
5
6
7
8
9
10
80
63
61
79
74
69
62
75
77
60
75
66
60
90
60
42
42
60
81
39
Height in
Subject Inches Temperament
11
12
13
14
15
16
17
18
19
20
64
76
71
66
73
70
63
71
68
70
48
69
72
57
63
75
30
57
84
39
Correlation and Causation
• Correlation does not prove causation
• Ex- negative correlation between self-esteem and
depression
– Heredity and brain chemistry might play a role
• Among men, length of marriage correlates positively
with hair loss- because both are associated with a
third factor.
– Age
– Correlation indicates the possibility of a cause and
effect relationship, but DOES NOT prove causation
Intuition Limit #976
• Illusory Correlation: the perception of
a relationship where none exists.
• Sugar makes kids more hyperactive
• Wet hair and cold hair cause a cold
• Don’t overgeneralize extreme cases GET
THE DATA!!
One last check……………..
You need to make sure your study is
reliable and valid.
1. Reliability-if your study was replicated
would you get the same results?
2. Validity- Does the study or experiment
test what it is designed to test.
Summing Up Surveys, Naturalistic Observation,
Case Studies, and Correlation Research
• All of these methods look to describe
the behavior not to explain it!
• Experimental Designed research is the
only research that gets at causation!
Random Sequences
Your chances of
being dealt either of
these hands is
precisely the same:
1 in 2,598,960.
Experimentation
and
Statistics
Experiments
Experimentation
• Experiments are the best way to isolate cause
and effect
– the investigator manipulates one or more factors
(independent variables) to observe their effect on
some behavior or mental process (the dependent
variable) while controlling other relevant factors
by random assignment of subjects
– by random assignment of participants the
experiment controls other relevant factors.
• Breast Milk Example
Experimentation
Research Strategies
• Double-blind Procedure
– both the subject and the research staff are ignorant (blind)
about whether the subject has received the treatment or a
placebo
– commonly used in drug-evaluation studies
• Placebo
– an inert substance or condition that may be administered
instead of a presumed active agent, such as a drug, to see if
it triggers the effects believed to characterize the active
agent
• Placebo Effect- the effect of positive thought and
willpower on an experiment
Experimentation
Research Strategies
• Experimental Condition
– The group that is exposed to the treatment, that
is, to one version of the independent variable (
real drug)
• Control Condition
– The group that contrasts with the experimental
treatment . Get the placebo, or possible nothing
– serves as a comparison for evaluating the effect of
the treatment
• Example- Viagra
Experimentation
Research Strategies
• Random Assignment
–assigning subjects to experimental
and control conditions by chance
–minimizes pre-existing differences
between those assigned to the
different groups
– Want similar age, attitudes…….
Experimentation
Research Strategies
• Independent Variable
– the experimental factor that is manipulated
– the variable whose effect is being studied
• Dependent Variable
– the experimental factor that may change in response to
manipulations of the independent variable
– in psychology it is usually a behavior or mental process
– It can vary depending on what happens during the
experiment
• Cause/effect…… If/Then
Experimentation
• Confounding Variables-
–Variables that cause changes in the DV
besides the IV
• Breast Feeding Example
• Operational Definitions
– Example Viagra
• IV- Viagra or placebo- time, amount
• DV- Sex- ………………………..
Experimentation
Problems• Sometimes not feasible or ethical
• 1. Obtain consent
• 2. Protect from harm
• 3. Confidential
• 4. Fully explain research after the exp.
• Animals?
• Results may not overgeneralize to other
contexts
Statistics
Describing Data
• Researchers first need to organize
their data
• Pie Chart, Bar graph
• Descriptive Statistics- describe the
data, but don’t focus or the
relationship
Percentage
still functioning
after 10 years
100%
99
98
97
96
95
Our Brand Brand Brand
Brand
X
Y
Z
Brand of truck
Percentage
still functioning
after 10 years
100%
90
80
70
60
50
40
30
20
10
0
Our Brand
Brand
X
Brand Brand
Y
Z
Brand of truck
Measure of Central Tendency
• 3 measures of Central Tendency- Mode , Mean
and Median
• Mode- the most frequently occurring score
• Mean- average
• Median- the middle score, when you arrange the
score in order from the highest to lowest
• Be Careful- can a few extreme score through off
any one of the central tendencies?
• What's wrong with- income for 62% is below
average
15 20 25 30 35 40 45 50
90
475
70
Mode Median
One Family
Mean
Income per family in thousands of dollars
710
Measures of Variation
• Need to know the variation in the data,
how diverse or similar the scores are
• Range– the gap between the highest and
lowest score
• Remember extremes scores can skew the
data
• 475,000 and 710,000
Measures of Variation
• The more useful measure is Standard
Deviation
–It gauges if scores are packed together
or dispersed
–Uses info from each score
–Smaller Standard Deviation for more
similar populations
–Higher Standard Deviation for more
diverse populations
When is an Observed Difference
Reliable?
• 1. Representative samples are better
than biased samples
• 2. Less variable observations are more
reliable than those that are more
variable
• Consistency
• 3. More Cases Are better than few
When is Difference Significant?
• statistical significance (p) is a measure of the
likelihood that the difference between groups
results from a real difference between the 2
groups rather than from chance
• If statistically significant …..the differences are
probably not due to chance
• Statistical significance indicates the likelihood
that a result will happen by chance. It does not
indicate the importance of the result
• The lower the P value, the less likely the results
are due to chance (P<.o1)