Kaili Sparks
The purpose of the project was to see if there is any correlation between grade point average and the
number of speeding tickets students have received. Our official research question was: Is the number
of speeding tickets a student has obtained related to their GPA? In order to get this data, we went to
every connect class and handed out a survey. The survey had the following questions:
1.
2.
3.
4.
5.
Do you drive?
Have you received any speeding tickets?
If so, how many?
Do you know your cumulative GPA?
If so, what is it?
We understood that many students may feel uncomfortable with these questions so we made sure that
the surveys were done anonymously. Unfortunately (or fortunately), many students have no speeding
tickets which makes our results not as interesting, and makes it hard to determine a correlation;
however, the results are shown below.
These are side by side graphs. The one on the left shows that 115 students had 0 tickets, 13 students
had 1 ticket, 4 students who had 2 tickets, and one student ad 6 tickets. The right graph shows GPA it is
great that it is leans to the right.
These are side by side boxplots. The one on the right shows that anything that is not 0 is considered an
outlier since no speeding tickets is the norm. The one on the right shows that the GPA does in fact lean
right. Three of the GPA’s were on the lower side so they are considered outliers.
These are the statistics for the speeding tickets. Notice all the 0’s.
Summary statistics:
Column
var1
Mean
Std. Dev.
0.20300752 0.67149085
Median Range Min Max Q1 Q3
0
6
0
6
0
0
These are the statistics for the GPA. Once again, Itineris students have fairly high GPA’s.
Summary statistics:
Column
var2
Mean
Variance
Std. Dev. Median Range Min Max Q1 Q3
3.5724525 0.14238004 0.3773328
3.7
1.8
2.2
4 3.4 3.8
And of course, we must focus on the main question. Is there are correlation? Below is the graph that
shows this along with the r value and equation.
Simple linear regression results:
Dependent Variable: var2
Independent Variable: var1
var2 = 3.5916767 - 0.094696485 var1
Sample size: 133
R (correlation coefficient) = -0.1685
R-sq = 0.028398724
Estimate of error standard deviation: 0.37335324
There seems to be some correlation. For n=100, the correlation value is .196. Since we have 33 more
samples and our r value is -.1685 it could be argued there is a negative correlation between the two.
Teens have gotten a bad name in driving; however, these results are promising. Perhaps better data to
collect would be number of accidents since I know of more people who have been in accidents than who
have a speeding ticket. Unfortunately, the project did not go as planned.
Our data table can be seen below:
0
0
0
0
0
0
0
0
0
0
0
3.6
4
2.88
3.8
3.8
3.3
3.3
3.979
4
3.8
3.8
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
0
0
0
0
0
1
0
3.66
3.8
3.9792
3.5
3.9
3.3
3
3.986
3.8
3.5
3.4
3.7
3.4
3.5
3.5
3.98
3.79
3.6
3.97
2.8
3.906
3.75
3.6
3.7
3.6
3
3.9
3.575
3.2
3.5
3.6
3.3
3.2
3.8
2.7
3.6
3.4
3.2
3.5
3.7
3.95
3
3.93
1
0
0
0
0
1
0
0
0
0
0
0
0
3.9
3.74
3.7
2.9
3.94
3.8
3.799
3.77
3.9
3.5
3.6
3
3.42
Number of Surveys Thrown Out for Various Reasons:
Number of Surveys Used:
48
133