Bivariate Data Analysis

Question 1

How can an association be described?

Answer 1

Associations are either non-existent (no association), linear (form a line), or non-linear (form a curve).

Question 2

If an association is linear, how do you determine the direction?

Answer 2

A positive association moes upward left-to-right, and a negative association moves down.

Question 3

How can we describe the strength of a scatterplot relationship?

Answer 3

It can be strong, moderate, or weak.

Question 4

How can you differentiate between the dependent and independent variable?

Answer 4

• 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.

Question 5

What does ‘r’ represent?

Answer 5

Pearson’s correlation coefficent, which shows the strength of a bivariate data relationship.

Question 6

Describe

r = 0.75 to 0.99

Answer 6

Strong positive association

Question 7

Describe

r = -0.75 to -0.99

Answer 7

Strong negative association

Question 8

Describe

r = 0.50 to 0.74

Answer 8

Moderate positive association

Question 9

Describe

r = -0.50 to -0.74

Answer 9

Moderate negative association

Question 10

Describe

r = 0.25 to 0.49

Answer 10

Weak positive association

Question 11

Describe

r = -0.25 to -0.49

Answer 11

Weak negative association

Question 12

Describe

r = -0.24 to 0.24

Answer 12

No association

Question 13

Formula

Line of best fit

Answer 13

y = mx + c

Question 14

Formula

m =

Answer 14

r(sy/sx)

r x (standard deviation of y / standard deviation of x)

Question 15

Formula

y-intercept of a line of best fit

Answer 15

c = ȳ - mx̄

y-intercept = mean of y - m x mean x

Question 16

Which statistics mode should be used for biveriate data?

Answer 16

2: A+BX