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Josh Woods
Professor Bodrero
Math 2040
Influences on Student’s GPAs
What has the greatest influence on college student’s GPA’s? This subject is important to
determine the factors that contribute most to a student’s success in school. If the most
important factors to a student’s success can be determined, then schools can focus their efforts
to instill these factors onto their students. These factors can then go on to help the schools
have a better success rate of college graduates. It is important to have a strong success rate of
college graduates, because of the need and benefit for college graduates in today’s economy. In
Holiday Hart McKeirnan’s article, “Higher Education and the American Workforce,” the author
states that, “Without college-level learning, American workers simply won’t have the
knowledge and skills they need to succeed in today’s global economy.” This shows the
importance of college graduates, and why it is important to determine what contributes most
to the graduation of a college student.
In this study, the relationship of different factors of college schooling and student’s
GPAs will be analyzed. This study will focus on the relationship of studying for exams and GPA,
and the relationship of how often a student visits the library to study and GPA. This study will
be using Snow College as its source of samples, 38 randomly selected students from Snow
College. The data for this study was collected by a survey administered to students who walked
into Snow College’s cafeteria, the Badger Den. The Badger Den is accessible to all students on

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campus, and this means the data is from all types of students on campus. The data from the
sample of 38 randomly selected Snow College students is what will be used to help determine
whether exam study time and library visits are beneficial to a college student’s success. The
results from this study cannot be used for inference of all college students or even all Snow
College students, because of the small sample size. What this study is designed to do, is help
encourage or discourage further advanced research into whether exam study time or library
visits are key factors in a student’s success. Snow College will be tested to see if it is a viable
college to conduct further advanced research. Also, exam study time and library visits will be
tested to see if further research is worth doing on these factors.
One of the first assumptions that is made about this study is that student success is
measured by GPA. This is not necessarily the only way to measure a student’s success, but is
the one used in this study. The next assumption that is made is that exam study time refers to
the average time in hours that a student studies for any one of their exams per week. In the
survey, it was not stated that the exam study time was per week, but it was implied. The next
assumption is that when the exam study time is being compared to Snow Colleges claimthat
students should study for classes for two hours for every one hour in class, that the mean of the
sample can be compared to just two hours. This is assumed because the survey asked for the
time the student studies for just one exam, and the claim talks about the study time for just one
class. Study time for exams is also assumed to be interchangeable with study time for the class,
because exams are part of the class.

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This is a scatterplot of the sample’s GPAs and exam study time per week. This
scatterplot also has a regression line, which helps determine the correlation between the
student’s GPAs and the time spent studying for exams each week. The data looks to have a
positive linear correlation. When the r value is calculated using the LinReg calculator function,
you get .326. This shows us that there is a positive linear correlation between student’s GPAs
and the amount of time they spend studying for their exams. Since the r value is only .326
though, there is not that strong of a positive linear correlation. This scatterplot with regression
line is important to this study, because it shows us the positive relationship between student’s
GPAs and the amount of time they spend per week studying for exams.
The next thing that this study tests, is if Snow College is a viable college to conduct
further advanced research on this matter. We did this by first doing a confidence interval on the
exam study time per week from the sample. This confidence interval helped determine the
predicted population exam study time per week based on our samples. This confidence interval
will be using a 95% level of confidence.
0
1
2
3
4
5
0 2 4 6 8 10 12
GPA
Exam Study Time Per Week (Hours)
Exam Study Time and GPA

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Calculator Function-> TInterval (List 1(sample of 38 Snow College student’s exam study times
per week), Frequency: 1, Confidence Level: 0.95 = (2.89, 4.53)
The results show that at the 95% confidence level, we can conclude that the true the
population mean for exam study time per week is between 2.89 hours and 4.53 hours. This
seems to exceed the expectations on Snow College’s website of how much students should be
studying for each class per week, “study a minimum of two hours outside of class for every hour
spent in class.” (snow.edu) To test if the sample mean was indeed greater than the expected
mean of two hours, a T-Test with a level of significance of 0.05 was done.
Calculator Function-> T-Test (mu=2, List 1(Sample of 38 Snow College student’s exam study
times per week), Frequency: 1, mu>2) -> P-value= 0.000074 < level of significance of 0.05,
Reject the Null Hypothesis that mu=2
At the 5% level of significance, we had enough evidence to conclude that the true
population mean of exam study time per week was greater than two hours. Based on the
sample, this shows us that students here at Snow College are studying more than what is
expected for each class per week. Although, it must be remembered that with this size of
sample, the sample should not be used to conclude for the entire population of students at
Snow College. The results simply help show that Snow College could be a good college for
further advanced research, because of the higher than expected average study times from the
sample of 38 Snow College students.
The next thing that this study covers is if the average GPAs of Snow College students are
greater than the national average of two-year public colleges. Gradeinflation.com indicates that

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the average GPA of two-year public colleges is 2.75. The test will be using a level of significance
that is 0.05.
Calculator Function-> T Test (mu=2.75, List: L1(sample of 38 Snow College student’s GPAs),
Frequency: 1, mu>2.75)-> P-value=0.000000067 < 0.05, Reject Null Hypothesis that mu=2.75
At the 5% level of significance, we had enough evidence to conclude that the average GPA of
Snow College students was greater than the average GPA of students at two-year public
colleges. The sample indicates that students at Snow College are getting better than average
grades. Again, this conclusion only indicates that Snow College could be a good college for
further advanced research into exam study times and library visits.
Based on our sample, exam study times per week has a positive linear correlation with
GPAs. This correlation is based on the scatterplot, regression line, and r value of the sample. It
was concluded that the population average exam study time per week for Snow College
students was greater than the expected study time of two hours outside of class for every one
hour in class. It was also concluded that the average GPA of Snow College students was greater
than the average GPA of two-year public colleges. All of these conclusions should not be used
to conclude for the entire population of Snow College, because of the small sample size. The
scatterplot and positive linear correlation indicates possible further advanced research into if
exam study time is a factor in a student’s success. The confidence interval and hypothesis test
help indicate that Snow College is possibly a good college to conduct further advanced research
on these factors. These tests and conclusions about Snow College possibly being a good college

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for further advanced research, are based entirely on the sample means of exam study time and
GPA being above average of the expected averages.
The next part of this study is to see if the amount of times a student goes to the library to study,
is a factor in the success of that student. This scatterplot and regression line helps give a visual
representation of the relationship between library visits and GPA. When we calculated the r
value, using the LinReg function on the calculator, we got a value of 0.08. This shows that there
is positive linear correlation between library visits and GPA. The r value is very small though, so
the positive linear correlation is not very strong at all. To test if there is enough evidence to
conclude that there is a positive linear correlation between library visits and GPA, a LinRegTTest
was performed. The level of significance that was used was 0.05.
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
0 2 4 6 8 10 12
GPA
Library visitsper week
Library Visits and GPA

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Calculator Function-> LinRegTTest (X List (sample of 38 Snow College student’s library visits),
Y List (sample of 38 Snow College student’s GPAs), Frequency: 1, rho>0) -> P-value=
0.32>0.05, Fail to reject Null Hypothesis of rho=0
At the 5% level of significance, we did not have enough evidence to conclude that there
was a positive linear correlation between library visits and GPA. This means that based on our
sample, we do not know if there is positive linear correlation between how many times Snow
College students visit the library per week to study and Snow College student’s GPAs. In order
to be able to use this conclusion for all of Snow College students, we need a larger sample size.
With a larger sample size, we also might be able to have enough evidence to conclude that
there is a positive linear correlation between library visits and GPA.
In discussion, this study was done entirely to help encourage or discourage the need for
more advanced research into factors that could help college students become more successful
in school. The factors that were examined in this study were exam study time and library visits.
Based on the conclusions in this study, more research should be done on exam study time and
library visits. This study also concludes that further advanced research should be done at Snow
College, because of the results of Snow College being above average in both average study time
and average GPA. With a larger sample size, a conclusion about the entire population of Snow
College could be made about the effectiveness of exam study times and library visits to a
student’s success. This further advanced research could then lead to similar studies at more
colleges. Eventually, a clear conclusion about the relationship between student’s success, exam
study time, and library visits could be made about all college students. This advanced research
could help colleges either focus more effort and money on helping students learn the

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importance of exam study time and library visits, or help colleges to focus their efforts and
money elsewhere. With colleges knowing where to focus their efforts and money more
effectively, student graduation rates should increase. This could then help the economy grow
stronger as there could be more college graduates entering the work force.
In conclusion, this study should not be used to conclude that exam study time and
library visits are beneficial to student’s success and graduation. Instead, this study should be
used to show professional researchers that it may be worth further advanced research into
exam study time and library visits, because of the benefits to college studetns. The reason that
further advanced research should be done is because of the conclusions that were outlined in
this study by the sample size of 38 randomly selected students at Snow College. With more
advanced research done by professional researchers into these two factors, college student
success and graduation rates could be increased as colleges could better understand where to
focus their efforts and money.

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Resources
Data:
Gender Year Exam
Study
Time
per
Week
GPA Library
Visits
per
week
F 1 2 3.8 0
M 1 7 3.5 3
M 1 5.5 3.8 9
O 2 6 3.7 3
M 1 5 3.87 1
F 3 5 3.5 4
M 1 3 3.95 1
M 2 6 3.8 10
M 1 5 4 5
M 2 6 3.6 1
F 2 0 3.4 0
M 2 5 2.75 4
F 1 2 3.5 0
F 1 5 3.8 0

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F 2 2 2.5 0
M 1 1 2 0
M 1 10 4 5
M 1 1 3.5 1
F 1 5 2.3 5
F 1 0 3.7 0
F 1 2 4 0
F 1 2 3.5 10
F 1 5 3.5 5
M 2 3 3.4 1
O 1 2 3.5 1
M 2 3 3.25 1
F 1 5 2.7 7
F 1 0 2.9 0
M 1 1 3 4
F 2 2 3.9 0
F 3 8 3.5 5
M 1 2 3 2
M 1 2.5 2 2
M 2 7 3.5 0
F 3 8 3.52 6

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M 1 1 2.5 1
M 1 2 2.7 3
F 1 4 3.4 2
Survey:
This is a survey for statistics 2040 that will help Josh Woods determine the study habits of
students here at Snow College. Your participation in this survey is completely voluntary, and all
data will only be used in complete confidentiality. This survey will consist of 5 questions and will
take approximately 2-3 minutes to complete. There are no foreseeable risks involved with
taking this survey. By responding to this survey, you are indicating that you are willing to
participate in this study. If you have any questions are concerns, please contact Josh Woods by
email at joshthescubadude@gmail.com.
1. What is your gender? ____ Male ____ Female ____ Other
2. What year are you currently in, here at Snow College?
____First year ____Second Year ____More than Two Years
3. On average, how many hours do you spend studying for your exams? ______
4. What is your current college GPA? Note, first semester students can estimate their GPA
based on the grades they currently have in their classes. ______
5. How many times a week do you go to the library to study? ______

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Works Cited
McKiernan, By Holiday Hart. "Higher Education and the American Workforce." AGB. N.p., 2016.
Web. 08 Nov. 2016.
https://www.snow.edu/catalog/registration.html
gradeinflation.com