2. Linear Regression
Involves two variables that are paired
because there is a relationship between
them
Deal with measurements made on two
variables X and Y - bivariate
Ex. height and weight, achievement &
learning approach, study habits &
grades, achievement and aptitude
3. Linear Regression
There is a straight line relationship
between variables X and Y
When X increases, Y also increases-
positive relationship
When X increases, Y decreases or vice
versa – negative relationship
5. Regression Line between achievement and
aptitude
Scatterplot: X v s. Y
Y = 14.379 + .85633 * X
Correlation: r = .98966
105
100
95
90
85
80
Y
75
70
65
60
55
40 50 60 70 80 90 100 110
X 95% conf idence
7. Relationship between Laziness and
Perseverance
Scatterplot: Y v s. X
X = 139.94 - 1.138 * Y
Correlation: r = -.9959
110
100
90
80
X
70
60
50
40
30 40 50 60 70 80 90
Y 95% conf idence
8. Y can be predicted based on
the value of X
Y = a + bX