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Psychology is a Science
Psychology is considered to be an empirical discipline. It is held to be based on objective observation. A central belief in psychology is that it is public knowledge--psychological truths are not based on secret insights, personal prejudices, or mystic experiences.
The Scientific Method
The scientific method is based on certain basic assumptions:
Note that these are assumptions--they cannot be proved. Can they be disproved? Our everyday commonsense understanding of life follows these assumptions fairly closely.
The scientific method is sometimes summarized as:
question: "Why are some people able to quit smoking while others fail?"
hypothesis: "The age at onset of smoking is negatively correlated with success in quitting"
test (experiment): Administer a survey to past and present smokers--"At what age did you start smoking?" Note: This is NOT an experiment
theory: Combine the results of many specific studies into a general conclusion
This summary misses the complex nature of each step and misses some of the fundamental dynamic character of science. Science relies on:
based on the 5 senses
done carefully to eliminate bias
should be reproducible (repeated observations are called "facts")
strictly speaking cannot establish causal relationships
essential to establishing causation
manipulation of one factor at a time
hypothesis = an educated guess about an observation that can be tested
makes use of deductive reasoning (drawing logical conclusions from a set of premises)
a series of repeatedly supported hypotheses can be combined into a theory
based on inductive reasoning (forming a general principle from specific observations)
subject to experimental refutation
Natural Laws and Explanatory Concepts:
allow prediction (sometimes quite precise though not usually in psychology)
consistent through space in time
should be consistent with each other and with observation
The scientific method is cyclical:
How do we evaluate science?
It helps to ask the following:
population = the entire group whose characteristics are being studied
It is not usually feasible to study the population as a whole
sample = a subset of the population
representative sample = a sample whose characteristics match those of the population
statistical analysis = procedures for extrapolating from observations on samples to conclusions about populations
based on probability (and algebra)
significant = unlikely to have occurred by chance
Relevant factors are called variables.
A relationship between variables is called a correlation.
positive = variable A increases along with variable B
negative = variable A decreases as B increases
correlation coefficient = a numerical indication of the degree of correlation (varies from -1 to +1)
Bias is a systematic source of error.
A central challenge in science, especially psychology is operationalization: How do we state our hypotheses in objectively verifiable form?
variables must be objectively, concretely, and usually quantitatively defined
characteristics must be reliably measured
easier to be invisible
difficult to control
easier to control
Measures of Behavior
cheap and easy
may not be true
questionnaire ("pencil and paper" instruments)
These do not involve the manipulation or control of any factor, and thus cannot be used to determine causal relationships.
Sometimes called descriptive or correlational.
a review of existing records
limited to available data
an examination of the history of a group of subjects (self-reported or directly observed)
current characteristics of a set of groups are examined; the group is then followed over time to see if the outcome is different for the different groups
non-intrusive (like the entomologist watching butterflies)
may be difficult to actually stay out of sight
intensive examination and description of a single individual
common and probably helpful in clinical settings
may be dramatic and interesting
may not be representative
may not be readily generalizable
These involve systematic manipulation or control of one (or more) factors, called independent variables.
This prior manipulation allows us to draw conclusions about causation.
If A tends to occur with B, there are three possible reasons:
A causes B
B caused A
C causes both A and B
Only an experiment will allow us to distinguish between these three.
In an experiment, we manipulate the variable of interest and control (keep the same) other variables.
In the simplest experiment we have a treatment group and a control group.
In the purest experiments, we change only a single variable.
If multiple variables are changed, we need to use statistical techniques to separate the effects of each.
If extraneous variables change from one test to the next, they may confound the results.
If there is no standardization of conditions we have an uncontrolled experiment.
Samples vs populations
We usually cannot study the entire population (ie, all people).
There are usually differences between different types of subjects
We try to pick a sample (a smaller group) of subjects that represent the population: a "representative sample."
To extend our findings with samples back to the population as a whole we use statistics.
A set of techniques that use mathematics and probability theory to draw conclusions from observations
These summarize observations
mean = average
median = the middle value
mode = the most common value
standard deviation = a number that expresses how spread apart a set of numbers is
95% of values fall within two standard deviations of the mean
correlation coefficient = a number that tells how much two variable go together
varies from -1 to +1
+1 = perfect positive correlation
-1 = perfect negative correlation
0 = no correlation
The "best fit" or "least squares" line (slope and intercept) can also be calculated.
These allow us to make inferences beyond the observations
For example, suppose that within a particular group of 100 children, girls scored higher than boys on a particular test. Does that mean that it is likely that another group of girls will also score higher than another group of boys?
From a given set of numbers (eg, scores) we can determine the probability that a certain distribution occurred by chance.
If the probability is less than some value, say 5% or 1%, than we say that the finding is statistically significant.
Examples of inferential statistics include t-value, F-value and the correlation coefficient (r)
Milgram's Famous Obedience Experiment (top)
Milgram wanted to answer the question "Can someone be coerced by an authority figure to hurt someone else?"
The Set Up:
On the face of it, the experiment looked at learning and had three participants: an experimenter, a teacher and a learner. The teacher and the learner were supposed to be experimental subjects who drew straws to determine roles. In fact, the drawing was rigged so that the one subject was always the "teacher." The learner was always the same person (a 47 year old accountant who had been thoroughly coached on his performance).
The learner was strapped into an electric chair. Both the teacher and the learner were told "Although the shocks can be extremely painful, they cause no permanent tissue damage."
The teacher sat in a different room where he could hear but not see the learner. The teacher gave the learner a simple word association test. When the learner answered wrong, the teacher was supposed to administer a shock.
The Shock Generator:
Milgram made a very convincing looking gizmo (see picture on p 627 in Feldman) with labeled switches for giving shocks at levels from 15 to 450 volts.
The teacher was given a sample shock using the switch marked 45 volts.
The switches were grouped from "Slight Shock" to "Danger: Severe Shock" (the last two were listed with "XXX").
When the switch was flipped, a red light came on above the switch, there was a click and a buzzing noise.
Each time the learner made a mistake, the teacher was told to move to the next voltage level. The teacher was supposed to announce the voltage level to the learner then flip the switch.
At various voltage levels the learner expressed discomfort then pain then agony. At 120V, he said "Hey this really hurts; at 270V he screamed and shouted "let me out of here." At 300 V he refused to answer anymore (which of course meant he got the question wrong). After 330V he stopped responding altogether (after complaining about his heart since 150V).
If the teacher did not want to continue, the experimenter said "The experiment requires that you continue" or "You have no choice, you must continue."
The experiment ended when the teacher refused to give any more shocks or 450V had been reached. Once the experiment was over, the set up was explained and the teacher and learner shook hands.
26 out of 40 subjects went all the way to 450V. No one stopped before 300V.
The subjects in Milgram's experiment were very distressed (even though they continued) and were greatly relieved when they heard about the hoax.
Milgram's experiment has been confirmed many times over.
Factors that Influenced Obedience in Milgram's Experiment:
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