Each week I will post a brief outline of the important concepts contained within the chapter. The
outline will serve as a reminder of what to focus on when you are reading the chapter.This week's
outline contains three important parts.
I. The Need for Psychological Science
A. Limits of Intuition and Common Sense ? There are two pitfalls in
thinking that make intuition and common sense untrustworthy
1. The Hindsight Bias
?I knew it all along? phenomenon
Ex. viewing a police lineup, expert testimony ? many errors in our recollection
2. Over confidence
Tendency to think we know more about an issue than we actually do and to
overestimate the accuracy of that knowledge.
B. The Scientific Attitude
Psychologists approach the world of behavior with skepticism, asking two
questions: What do you mean? How do you know? Next time you read the
newspaper or hear something on TV try it.
Critical Thinking: thinking that does not blindly accept arguments and
conclusions.
Critical thinkers always ask questions
C. The Scientific Method
Includes making observations, forming theories, refining theories
Theories: explain, organize, and predict the behaviors or events under study
Theories: give direction to research by generating testable predictions, called
hypotheses.
To be certain that our observations are not biased by what we think
psychologists report their research with operational definitions, a statement of
the procedures used to define research variables. We use operational
definitions so others are able to replicate our work.
Replication, repeating the essence of a research study, usually with different
participants in different situations, to see whether the basic finding
generalizes to other participants and circumstances.
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The three basic research strategies in psychology are DESCRIPTION,
CORRELATION, and EXPERIMENTATION
II. Description
The simplest research strategy
Psychologists describe behavior using case studies, surveys, and naturalistic
observations.
A. Case Study
An observation technique in which one or more persons is studied in great
depth in the hope of revealing general principles underlying the behavior of all
people.
ADVs and DISADVs
B. The survey
Commonly used in descriptive and correlation studies.
Measure the self-reported attitudes or behaviors of a randomly selected
representative sample of an entire group or population.
ADVs and DISADVs :
1. Wording effects: How do you ask questions?
2. Sampling: Choose a representative sample. Make it a random sample.
· Ex. How would you survey the military in Europe? 1) Survey all of them?
NO you would survey a representative sample of the total military population (all the
cases in the group)
· How do you make your sample representative of this population? You make it a
random sample; every person in the entire group has an equal chance of
participating.
· Ex. In the upcoming presidential primaries think critically about the information you
hear. Was the sample a representative or unrepresentative sample?
·Ex. Sampling voters in a national election survey is like sampling the beans in a jar.
The fastest way to know their ratio is to blindly transfer a few into a smaller one and
count them. This is called random sampling.
C. Naturalistic Observation
Seeks to observe and record the behavior of organisms (including humans) in
their natural environments.
ADVs and DISADVs
III. Correlation
Statistical measure of a relationship, revealing how accurately one event
predicts another
Graphically represented as scatter plots
Positive correlation indicates a direct relationship in which two things increase
or decrease together
Negative Correlation indicates an inverse relationship in which one thing
increases as the other decreases
Ex. As your level of test anxiety goes down as your time spent studying for the
exam goes up, would you say these events are positively or negatively
correlated?
Zero Correlation no relationship exists
A. Correlation and Causation
Correlation DOES NOT prove causation!!!
A third factor may cause low self esteem or depression
IV. Experimentation
Explains cause and effect
Allows researchers to do two things: 1) manipulate one or more factors of
interest ? independent variable (IV) and 2) observe the effects of another
behavior by holding it constant ? dependent variable (DV).
A. Evaluating Therapies
In a typical experiment, subjects are randomly assigned to either a control
condition, in which the experimental treatment is absent, or an experimental
condition, in which the treatment of interest is present.
Random assignment equalizes the two groups in age, attitudes, and many
other characteristics. With random assignment we can know that any later
differences between people in the experimental and control conditions must
be the result of the treatment.
Two other control techniques involve use of placebo and the double-blind
procedure.
Placebos look like the treatment, but are not ? sometimes referred to as a
sugar pill
Double-blind both the research participant and the research staff are ignorant
(blind) about whether the research participants have received the treatment
or a placebo.
V. Statistical Reasoning
A. Describing Data
organize data as in bar graphs
B. Measures of Central Tendency
Summarizes data
Three measures of central tendency: mean, median and mode.
Mean: arithmetic average; sum of all scores divided by the number of scores.
The mean is the most commonly reported measure of central tendency. It is
extremely sensitive to unusual scores and therefore is potentially misleading
as a representation of the average of a distribution that is skewed
Median: middle score (half above and below); score that falls at the 50th
percentile. The point that divides the distribution into two parts such that an
equal number of scores fall above and below that point.
Mode: most frequently occurring score
Ex. Comparison of mean and median
Scores Mean Median
1,2,3,4,5 3 3
1,2,3,4,50 12 3
1,2,3,4,100 22 3
Ex. 7 members of the girl scouts reported the following individual earnings from their
sale of cookies:
$s 2, 9, 8, 10, 4, 9, 7
Mean = 7
Median = 8
Mode = 9
C. Measures of Variation
Range of scores: difference between the highest and lowest scores in a
distribution; simplest measure of variation ex. 11,7,21,14,7 , the range is 14
Standard deviation: how much a score deviates around the mean score
D. Making Inferences
1. When is a difference reliable?
a. Most reliable inferences about a population are based on a
representative sample.
b. Averages derived from samples with low variability are more reliable
than those based on samples with high variability
c. Averages based on more cases are more reliable than averages based
on only a few cases
2. When is a difference significant?
Statistical significance: the difference observed is not due to chance.
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