Experiments vs NonExperiments
• An experiment is any study
in which a treatment is introduced.
– A new method of teaching
• A nonexperimental study does
not introduce a treatment.
– Comparing opinions from natural
groups
Experiments
• Any study
in which a treatment is introduced is an experiment.
• Control:
Scientists investigate the effect of various factors one at a time in an experiment.
• An experiment
has at least one independent variable and at least one dependent variable.
• A true experiment
involves random assignment of participants to treatment groups.
Treatment Groups
• Experimental Group: group receiving
treatment
• Control Group: group not receiving
treatment
– Represents expected results
for experimental group if no treatment is given
– Represents population before
treatment or if no treatment.
• Secondary Experimental Group:
receives treatment of lesser interest
Randomization
• True experiment involves assignment
to treatment groups based on random selection
• All participants have equal
chance of being chosen for experimental group or control group
• The larger the number of participants
the greater the chance that groups will represent the population
Basic Terms of Sampling
•
Population: set of all cases of interest. For example:
• current students at your institution
• current residents of your city
• citizens of the United States
• citizens in North America
• Sampling
Frame: list of the members of a population.
• For example, registrar’s list of all currently
registered students
• Sample: subset
of the population used to represent the population.
• Students in your class as a sample of current
students at your institution (or your city, United
States, North America)
• Element:
each member of the population.
Obtaining a Sample (continued)
• Goal: Sample
should represent the population.
– Characteristics of participants in the sample should be
similar to those of the entire population.
– Example: Which sample represents a population that is 30%
freshman, 30% sophomore, 20% junior, 20% senior?
Sample A
Sample B
30 freshmen, 30 sophomores,
60 freshmen, 60 sophomores,
20 juniors, 20 seniors
40 juniors, 40 seniors
Both! But note: The samples are representative on one feature only!
Obtaining a Sample (continued)
• A biased sample occurs
when the characteristics of the sample differ systematically from those of
the target population.
– A sample may underrepresent a segment of the population, or
– overrepresent
a segment of the population.
• For example, most samples in psychology research
overrepresent college students and underrepresent individuals who are not in college.
• Most research underrepresents individuals from
diverse cultures.
Approaches to Sampling
• Sampling refers to the procedures used
to obtain a sample.
• Two basic approaches to sampling
are
– nonprobability sampling, and
– probability sampling.
Approaches to Sampling (continued)
• Nonprobability sampling: No
guarantee that each member of the population has an equal chance of being included in the sample.
• “Convenience sampling” occurs when the researcher selects individuals
who are available and willing
to respond to the survey.
– Examples: Magazine surveys, Internet surveys
• Lots of psychological research uses convenience samples (but this can be OK).
Approaches to Sampling (continued)
• Probability sampling:
All members of a population have an equal chance of being selected for the survey (this is called a “simple random
sample”).
• Need to have a sampling frame (list) of people
in the population, or
• use randomdigit dialing (but not all members
of the population may be included).
Approaches to Sampling (continued)
• Stratified Random Sample: The population
is divided into subpopulations called “strata.”
• Random samples are then drawn
from the strata.
• Stratified random sampling
increases the likelihood that the sample will represent the population.
Variables
• Trait or characteristic with
two or more categories
– Participants vary in terms
of which category they belong
• Categories
should be mutually exclusive
– Each participant belongs to
one and only one category
• Categories
should be exhaustive
– Variable has a category for
each participant
Independent Variable
– Independent Variable (IV):
A factor that researchers control or manipulate in order to determine the effect on behavior.
• A minimum of two levels: The treatment (experimental)
condition and the control condition
• Secondary treatment level is preferred
• Presumed to be the cause
Dependent Variable
– Dependent Variable (DV): The
measure of behavior that is used to assess the effect of the independent variable.
• In most psychology research, several dependent
variables are measured to assess the effects of the independent variable.
• Presumed to be the effect of treatment
Experimental Design
• Design 1:
– Group A R O X O
– Group B R O
O
• Design 2:
– Group A R X
O
– Group B R
O
• Solomon Randomized 4group
Design:
– Group A R O X O
– Group B R O
O
– Group A R
X O
– Group B R
O
Experiments
• Look for Cause and Effect Relationships
• Must make effort to eliminate
plausible alternative explanations for differences between Experimental and Control Groups
• No randomization
with treatment is still an experiment, but not true experiment.
NonExperimental Studies
• Variables are often still referred
to as IV and DV
• Independent Variable
– One presumed to be cause
– Observed first
– Better referred
to as Predictor
• Dependent Variable
– One presumed to be effect
– Observed later
– Better referred
to as Criterion
