### Point Biserial

```Point Biserial Correlation Example
• A researcher wishes to determine if a significant
relationship exists between the gender of the
worker and if they experience pain while
• The independent variable is the question which
female” (Dichotomous)
• The dependent variable is from the question that
asks “How many years have you been performing
Step 1: Data Setup
• The independent variable is the “x” variable and
the dependent is the “y”.
X
Case
Gender
Y
Number of years
1 M
10
2 M
11
3 M
6
4 M
11
5 F
4
6 F
3
7 M
12
8 F
2
9 F
2
10 F
1
Hypothesis Setup
• Ho: There is no relationship between the
number of years performing the tasks and the
workers’ gender.
• H1: There is a significant relationship
between the number of years performing the
• Use an Alpha Level=.05
Point Biserial Correlation Formula
The correlation coefficient of .87 is a strong correlation. We must use a
T-test to determine if it is significant.
Is the Correlation Significant?
• Now we need to determine if the correlation
coefficient of .87 is significant.
• This is done by performing a t-test.
T-test for Correlations
To interpret the .87, compare the 5.11 to the critical score. If the obtained score is
greater than the critical score, reject the Null and accept the alternative. The critical
score from the t-table at .05 and DF = 8 is 2.31. (NOTE: On a T-table, use the .025
column since .025 at one end and .025 at the other end gives you .05).
T-Table
The critical score from the t-table at .05 and DF = 8 is 2.31. (NOTE: On a T-table, use the
.025 column since .025 at one end and .025 at the other end gives you .05).
Conclusions
• Since 5.11 is greater than 2.31, Reject the Null
Hypothesis and conclude there is a significant
relationship between gender and the number
of years working at the task.
• There is a significant relationship between the
genders of the workers the number of years
performing the task. Males have been
performing the task significantly longer than
females.
```