SOCB06 chapter 10:
Correlation: age, intelligence and education attainment vary from one person to another and therefore
referred to as variables.
Many relationships are statistically significant- stronger than you would expect to obtain just as
a result of sampling error alone.
Correlations vary with respect to their strength, we visualize differences in strengths of
correlations by means of a scatter plot or scatter diagram, a graph that shows the way of scores
on any two variables, X and Y, are scatter throughout the range of possible score values.
Scatter plot: set up as the X is arranged horizontally, Y is measured across the vertical line.
- Directions of Correlation:
It can be either positive or negative in terms of direction.
Positive correlation: respondents getting high scores on the X variables also tend to get high
scores on the Y variable.
Negative correlation: respondents have high scores on the X variable and low scores on the Y
variable. Such an example is education and prejudice.
- Curvilinear Correlation:
One variable can increase while the other increase, until the other reverses itself so that one
variable can increase while the other decrease.
Correlation Coefficient: expresses both strengths and weakness and direction of straight-line
correlation. You have -1.00 and +1.00.