Bivariate Data Analysis Flashcards
How can an association be described?
Associations are either non-existent (no association), linear (form a line), or non-linear (form a curve).
If an association is linear, how do you determine the direction?
A positive association moes upward left-to-right, and a negative association moves down.
How can we describe the strength of a scatterplot relationship?
It can be strong, moderate, or weak.
How can you differentiate between the dependent and independent variable?
- The independent variable is more likely to be in clear divisions, like jumps of ten.
- The independent variable is shown in the top row or left column of the table of values, whil the dependent variable is on the bottom or right.
- The independent variable is represented on the horisontal axis, the dependent on the vertical.
What does ‘r’ represent?
Pearson’s correlation coefficent, which shows the strength of a bivariate data relationship.
Describe
r = 0.75 to 0.99
Strong positive association
Describe
r = -0.75 to -0.99
Strong negative association
Describe
r = 0.50 to 0.74
Moderate positive association
Describe
r = -0.50 to -0.74
Moderate negative association
Describe
r = 0.25 to 0.49
Weak positive association
Describe
r = -0.25 to -0.49
Weak negative association
Describe
r = -0.24 to 0.24
No association
Formula
Line of best fit
y = mx + c
Formula
m =
r(sy/sx)
r x (standard deviation of y / standard deviation of x)
Formula
y-intercept of a line of best fit
c = ȳ - mx̄
y-intercept = mean of y - m x mean x
