2. Correlational Research
• discover, and then measure the relationship between two or more
variable
• It seeks to relate the traits, abilities or conditions of one variable to
another
- Sample research question on traits: What is the relationship between
population and voting turn outs?
- Sample research question study on abilities: Is there a significant relationship
between advertisement expenses and voting turn outs?
- Sample research question on conditions: Will an increase of poverty rate
increases voting turn outs?
3. Statistical Assessment of Relationships
Dependent Variable Data
Are the Dependent variable data quantitative or nominal?
quantitative
nominal
Correlation Analysis: r
Do you have more than two independent variables?
No Yes
Regression Analysis: R Log-Linear Analysis
Logistic Regression
Midterm Coverage
5. The Pearson Correlation Coefficient (r)
Formula of r
r =
]
)
(
][
)
(
[
)
)(
(
2
2
2
Y
Y
X
X
Y
Y
X
X i
i
Hypothetical Data
Year X Y
2002 4 4
2001 4 3
1999 3 2
1997 2 2
1995 2 1
1
N
Z
Z Y
X
=
=
N
Y
Y
N
X
X
N
Y
X
XY
2
2
2
2
For those who want to solve
manually you can use this
formula
Let: X= advertisement expenses in Billion pesos
Y=voting turn outs in billion person
6. Interpretation of r
If the relationship between X and Y are positive:
If the relationship between X and Y are negative:
-1< r <1
0 < r < 1
-1 < r < 0
If p-value associated with the r is < .05
The variable X and Y are significantly correlate to each other.
Positively: 0 < r < 1, Negatively -1 < r < 0
If p-value associated with the r is >. 05
There is no significant correlation between X and Y
7. Reporting Correlations/ Correlation Analysis
“ As predicted by the research hypothesis, the variable of advertisement expenses
and voting turn outs were (significantly) positively correlated
in the sample (the data), r(20) = .52, p < .10
Wherein, an increase of advertisement expenses will increase voting turn outs.
r(Number of Participants) = Correlation Coefficient r, p < alpha
