Module 9: Conducting Correlational Research Flashcards
Magnitude
the strength of the relationship. This is determined by the correlation coefficient (from -1.00 to +1.00)
Scatterplot
can be used to make a visual representation of the relationship between two variables
4 basic patterns of scatterplot
- positive correlation
- negative correlation
- no relationship (intelligence and weight)
- curvilinear relationship
Positive correlation
shows that an increase in one variable is related to an increase in the other and vice versa
- smoking and cancer
Negative correlation
indicates that an increase in one variable is accompanied by a decrease in the other variable. This correlation represents an inverse relationship
- mountain elevation and temperature
Curvilinear relationship
A correlation coefficient of 0 indicates no meaningful relationship between two variables. However, it is also possible for a correlation coefficient of 0 to indicate a curvilinear relationship. The strong positive relationship depicted in the left half of the graph essentially cancels out the strong negative relationship in the right half of the graph.
- memory and age
Causality
refers to the assumption that the correlation between two variables indicates a causal relationship
Third-variable problem
results when a correlation between two variables is dependent on another (third) variable.
Using partial correlation to remove the third variable.
Partial correlation
It is possible statistically to determine the effects of a third variable by using a correlational procedure known as partial correlation, which involves measuring all three variables and then statistically removing the effect of the third variable from the correlation of the remaining two.
Restrictive range
A variable that is truncated and has limited variability
Person-who argument
Arguing that a well-established statistical trend is invalid because we know a “person who” went against the trend
