|
|
Non-experimental |
Experimental |
|
Correlational |
Differential(Correlational) |
Quasi-experimental |
True Experiment |
|
Manipulation |
No manipulation of variables. |
No manipulation of
variables.
|
Manipulation of the independent
variable |
Manipulation of the independent
variable |
|
Subjects |
Subjects are NOT assigned to groups. Usually, there is only ONE
group of subjects. However, subjects are Randomly SELECTED for
participation. |
Subjects cannot be randomly assigned to groups. The groups of
subjects differ on some PRE- EXISTING
variable (ex: gender)
Subjects should still be randomly
selected for participation
|
Subjects are NOT randomly assigned to control and experimental
groups because it is logistically difficult (e.g., comparing 3rd
period and 5th period AP psych classes
after each class has be "treated" differently.) But, there
are control & experimental groups in this type of design....just no
random assignment.
If possible, they should be randomly
selected for participation.
|
Subjects are randomly assigned to control and experimental
groups.
(Ex: control group gets regular teaching and the experimental group
gets new teaching method)
If possible, they should be randomly selected for participation. |
|
Variables |
Two variables (X and Y) are measured and the STRENGTH and
DIRECTION of the RELATIONSHIP is determined.
(Ex: measuring GPA and depression level) |
Subjects are divided into groups based on a pre-existing variable
(X) (such as sex, religion, etc.) and compared on some other variable (Y)
(i.e., IQ, self-esteem, depression, anxiety, etc.). |
Subjects are in pre-formed groups. But, unlike correlational and
differential research, an independent variable (IV) is manipulated
and the groups are measured & compared on a dependent
variable (DV). (Ex: Using one teaching technique with 3rd
period and a new technique with 5th period. Then the two
classes would be compared on final grades (the DV) to see if a statistically
significant difference existed) |
The Independent variable (IV) is manipulated and
the dependent variable (DV) is measured. The
groups’ scores on the dependent variable are then COMPARED to
determine if a STATISTICALLY SIGNIFICANT DIFFERENCE EXISTS.
|
|
Statistics |
Pearson product-moment, correlation (Pearson’s r) |
Chi-square, t-test, ANOVA, point-biseral
correlation
|
Chi-square, t-test, ANOVA |
Chi-square, t-test, ANOVA |
|
Conclusions |
Variable X co-varies with variable Y (i.e., there is a relationship between
the two variables.) Cause and effect
cannot be proven.
|
Differences in variable X may be RELATED to the differences in
variable Y, but cause and effect cannot be proven. |
While we may be able to draw some causal conclusions, we can’t
do it with as much confidence as if we had used a TRUE experimental
design. (This is due to lack of random assignment and other controls). |
Changes in the IV CAUSED changes in the DV. We can be most
confident when we have controlled for as many threats to internal
validity as possible. |