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Notebook Tabs
1. Prologue/Chapter 1
2. Chapter 2
3. Chapters 3 and 4
4. Chapters 5 and 6
5. Chapters 7
6. Chapter 8
7. Chapters 9 and 10
8. Chapters 11 and 15
9. Chapters 12 and 13
10. Chapters 14
11. Chapters 16 and 17
12. Chapter 18
AP Psychology: Chapter 1: Thinking
Critically With Psychological
Science
Discussion Question
What is critical thinking?
How does it relate to
psychology and this
course?
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
relationships that help predict
behavior
3.
Experimental-doing studies that
help explain behavior
Research Methods- Descriptive

Case Study
an observation technique in which
one person , or a small group, 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 cigarette ads or pornography be allowed
on television?
Ex. Mississippi River- Is the Mississippi River longer or
shorter than 500 miles? How long is the Mississippi
River?
Is the Mississippi River longer or shorter than 3000
miles? How long is the Mississippi River?
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
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Correlation and Causation
 Correlation

Ex- negative correlation between self-esteem and depression


does not prove causation
Heredity and brain chemistry might play
a role
Among men, length of marriage correlates positively with hair lossbecause 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.
Arthritis and cold weather
Sugar makes kids more hyperactive
Wet hair causes a cold
Pregnant cravings and sex of the child
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…NEXT TIME!
Random Sequences
Your chances of
being dealt either of
these hands is
precisely the same:
1 in 2,598,960.
Warm
Up
Come up with one statement that would indicate a positive correlation.
1.
2.
3.
Come up with one statement that would indicate a negative correlation.
What do these numbers tell you about the relationship
1.
+ .95
2.
-.19
3.
+ .65
4.
-.02
4. List 1 pro and 1 con of Correlational Research.
5. What do these graphs tell you about the variables
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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
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
Research Strategies

Experimental Condition


Control Condition



The group that is exposed to the treatment,
that is, to one version of the independent
variable ( real drug)
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

Double-blind Procedure



Placebo


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
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

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- ………………………..
Ethics
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
Descriptive Statistics Researchers
first need to
organize their data
Pie
Chart, Bar graph
Organize
& describe the
data, but don’t focus on 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 –
neatly summarizes data
 Mean-
average
 Most commonly
 Biased by a few
reported
extreme scores
 Median-
the middle score, when you arrange the
score in order from the highest to lowest
 50th
percentile
 Mode-
the most frequently occurring score
 Be
Careful- can a few extreme scores throw off any one
of the central tendencies?

What happens to the mean income of a café when Bill Gates sits
down???
 What's

wrong with income for 62% is below average
British newspaper headline
Illustration of measure of central
tendency
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.
2 ways- Range and Standard Deviation
Range– the gap between the highest and
lowest score
Remember extremes scores can skew the
data
475,000 and 710,000 – illustration from
previous slide
Find the mean, median, mode and
range
5, 16, 2, 7, 4, 11,2,2
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 Data
 Higher Standard Deviation for more
diverse Data
 Results
are not consistent
 Standard
variance
deviation is the square root of
Which of the following sets of numbers has the
highest standard deviation
A.
-2,-1,0,+1,+2
B.
1.00,1.25,1.50,1.75,2.00,2.25,2.50,2.75,3.00
C.
2,6,10,14,18
D.
5.756,5.765,5.890,5.923
E.
91,92,93,94,95
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Normal Bell Curve

Percentage of scores within 1 standard deviation = 68%

Percentage of scores within 2 standard deviations = 95%

Percentage of scores within 3 standard deviation = 99.7%
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Sample Question
Question: What would be the
percentage breakdown for one standard
deviation of 15 points on an IQ test with
the mean of 100
Example Question: one standard deviation of 15 points on an IQ test with the
mean of 100 , would mean 68% of your results are within 85 and 115 points
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Look at the mean and median…
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Look at the mean and median…
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
Score are more consistent
Low small standard deviation or
low range
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