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A Basis For Grade Point Average:
A Study of the Relationship between a
student’s grade point average and the

number of hours sleep.

A research conducted by
Willie J. Thompson Jr.
December 2008

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Introduction

In the university culture the grade point average is a key indicator of a successful

college career and vice versa. Most students would agree that in order to achieve the

highest grade point average, various conditions have to be met: a balanced course load,

consistent interaction with professors and staff, encouragement from a supporting family

or network and lastly, proper rest and relaxation. However many students have found

proper rest, or adequate sleep amounts to be a challenging area to conquer. This study

seeks to present findings about sleep hours as a key determinant of student’s grade point

average. In the preparation for the work force, a college student experiences could vary

from stressful situations, high campus involvement to depression, fear, and separation

anxiety. But does the lack of sleep can affect academic performance on any level?

Problem

Our question here is to understand the relationship between a student’s grade

point average and the number of hours sleep. The Grade point average (hereafter GPA) is

a number that represents the average of a student’s grades during his or her time at an

institution, and usually weighted by a number of credits given for the course. Most

colleges and universities in the US use a four-point system. And the GPA is sometimes

used as a determining factor of the student’s ability to engage further academic material

and the acquisition of graduate and post graduate degrees. However sleep is defined as

the innate state of bodily rest and is suggested by scientist as needed for survival.

Anderson A. Zagler, found that sleep deprivation affects the immune system and

metabolism (Zagler R504-R509.)i. Zagler’s study also shows numerous ways in which

sleep is related to memory processing, preservation, stating a person is most safe when

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asleep. Engaging the above factors and comparing them to the experiences of the average

college student. This study has significance to the student who engages in a loaded course

of study and a sharp memory is needed during examination and testing seasons. This

study is scientifically significant for its uncommonness. Julian R. Betts and Darlene

Morell conducted a study the relative importance of family background, high school

resources and peer groups as determinant of GPA, but hours of sleep were not

considered. It causes this study to explore the hours of sleep a student gets, and its affect

on academic measuring systems such as GPA.

Hypothesis & Theory

It is hypothesized that the numbers of hours of sleep will have an inverse affect on

GPA. It is speculated that the hours sleep each respondent gets will affect the hours

engaged in rigorous academic work, therefore impacting the students GPA. As the

college student is in need of well rested functioning faculties’ to satisfy academic

requirements that are measured by the GPA.

Specifically, the study will explore: if the hours of study, hours working for an

employer, and if the respondent experiences trouble sleeping, all affect both the

respondents sleep hours and GPA; the on/off campus living situation can affect the

respondents sleep hours; and lastly the type of high school a student graduated from and

the respondents head(s) of household highest level of education can impact the GPA as

listed in Figure 1 below:

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Figure I. Analytical Model of Relationships among Hours Sleep and Grade Point

Average and Other related Variables.

Methodology

The handed survey research design was chosen to gather data for this problem.

This process is where questionnaires were distributed by hand, completed by respondents

and returned to data collector by hand. This allows for a personal connection between

respondent and collector, is found to be cost efficient, and easily managed by the

collector. This also allows the data collected to be free of possible confidentiality

Hours of
Study

Hours Working
for an

Employer

Hours
Sleep

GPA
Residency

On/Off
Campus

High
School

Attended

Head(s) of
Household

Highest
level of

Education

Trouble
Sleeping

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breaches, and destruction. The handed subtype does have drawbacks in which the

respondent might not feel comfortable sharing answers to certain questions with the

collector even though the questionnaire is anonymous and the respondent attitude, attire,

and presentation may be a factor in the distribution process.

Selection of the study participants were completed through two non-probability

processes called availability and quota sampling. The former sampling method is also

known as a haphazard, accidental, or convenience sample (Schutt 2006).ii This research

sampling consists of random number of freshmen, sophomores, juniors, seniors and

graduate students, both male and female. Data collectors went to certain buildings or

areas on the campus of Howard University and simply asked students who were available

to complete the survey, once all surveys were handed out and returned the sampling

process was over. The benefit of availability sampling it is convenient is easily

administered. The disadvantage to availability sampling is the prejudice the research staff

may have to the work/class schedules of respondents.

Quota sampling is intended to overcome the most obvious flaw of availability

sampling—that the sample will just consist of whoever or whatever is availability,

without any concern for its similarity to the population of interest (Schutt 154.)iii. This

research sampling consists of an equal number of freshmen, sophomores, juniors, seniors

and graduate students, both male and female. Data collectors went to certain buildings, or

areas on the campus of Howard University and simply asked students who fit the

characteristics to complete the survey, once the quota was reached the sampling process

was over. The benefit of quota sampling is the narrowed focus and is easily administered.

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The disadvantage to quota sampling is the limited research the findings will provide. It is

not representative of the entire population, and it dispels random selection.

Table 1 below, presents the demographics of the respondents to the questionnaire:

61% of the respondents were female; 36% of the respondents were from homes whose

parent(s) held a bachelors degree; 162 respondents parents share a family income of less

than 40,000; and 502 of them grew up in suburban/rural areas.

Table 1
Demographic Characteristics of Sample

Demographic Characteristics Frequency Percent

Gender

Female 619 61.0
Male 367 36.2
Total 986 97.2

Education of Family Head

No college degree 310 31.7
Bachelors degree 373 36.8
Master’s degree or higher 295 29.1
Total 978 96.4

Annual Family Income
Less than $40,000 162 15.9
$40,000 to $59,999 156 15.4
$60,000 to $79,999 153 15.1
$80,000 to 99,999 138 13.6
$100,000 to 149,999 126 12.4
$150,000 or higher 95 9.4
Total 830 96.4
Median: $70,000

Type of Area Grew Up In
Urban 474 46.7
Suburban/Non Urban 502 49.7
Total 976 96.3

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To collect data a questionnaire was designed by the fall 2008 Sociological

Methods class under the guidance of Dr. Johnny Daniel. A total of 8 questions were

asked to aid us in our understanding of the relationships among hours sleep and grade

point average and other related variables. Specifically: How many hours a week, on

average, do you spend studying, and measured on a scale ranged from less than 1 hour to

40 hours or more? Please indicate whether you experienced trouble sleeping during this

semester and asked to check if applicable? Was your high school public or private which

included the option of other? Do you live on-campus or off-campus, as a yes-on or no-off

measurement? How many hours of sleep do you get on an average night, and asked to

write in response? Which category best represents your overall grade point average,

measured on a scale ranging from 0= GPA not established to 12= 4.0? What is your

classification with choices ranging from freshmen to graduate or professional student?

And, what is the highest level of education the head(s) of your family household received

measure by a range from Elementary school diploma to Degree beyond the bachelor’s

degree?

The advantages to these questions were they were all closed ended and refined by

the professor. The questions maintained a consistent focus, and were not tedious, boring,

or lengthy. The disadvantages could have been the opened ended questions in which

respondents could not circle but have to give careless written responses.

To data was analyzed on an aggregate basis, in which all responses are combined

for the purpose of explanation, description or evaluation. This quantitative research uses

statistical procedures: univariate (frequency and percent distribution of grade point

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average, (hereafter DV), bivariate (percent distribution of hours of sleep, (hereafter KIV),

variance, range, mean, mode, correlation, t-test, ANOVA, and regression checks.

Findings

The GPA of a student is simply a measuring rod of all the academic course work a

student has engaged in at an institution. In the administered questionnaire the Howard

University grading system ranged from GPA not yet established to 4.0, which is an A.

Students were asked to identify which category best represents their overall grade point

average this variable indicated here is the dependent variable.. The chart below describes

a percentage distribution of the respondents GPA.

In Table 2, the pattern of the distribution of GPA’s according to shows the modal

category for respondents is GPA category 2.6 to 2.9. The mean GPA for the respondents

is 3.1.

Table 2
Frequency Distribution and Percentage Distribution of

the Grade Point Average
GPA Frequency %

2.5 or less 73 8.3
2.6 to 2.9 181 20.6
3.0 to 3.1 147 16.7
3.2 to 3.3 151 17.2
3.4 to 3.5 131 14.9
3.6 to 3.7 101 11.5
3.8 to 4.0 96 10.9
Total 880 100
Mean 3.1

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In Table 3 we find a cross tabulation between the respondents grade point average

and hours of sleep. This table shows that there is almost to no relationship between the

KIV and DV. The chi square test reads only a .099% of non-significance.

Table 3
Percentage Distribution of the GPA by the R Hours Sleep

Index of R

Hours Sleep

Index of GPA
– 5 hours 5 hours 6 hours 7 hrs 8 hrs 9 hrs +

2.5 or less 7.6 10 7.7 4.7 5.7 15.2
2.6 to 2.9 24.1 23.3 19.9 15.3 28.6 17.4
3.0 to 3.1 17.7 20.7 17.6 15.3 12.4 17.4
3.2 to 3.3 21.5 18 13.5 21.2 20 13
3.4 to 3.5 13.9 11.3 17.9 15.9 10.5 10.9
3.6 to 3.7 5.1 10 11.5 13.5 15.2 8.7
3.8 to 4.0 10.1 6.7 11.9 14.1 7.6 17.4
Total 100 100 100 100 100 100
Number 79 150 312 170 105 46

Chi-Square= 40.324^, df=30, p=.099

During the t-test the entire group of respondent is divided in two, by the number

of hours sleep. Group 1 (getting 5 to 6 hours of sleep) is 4.00 and the mean for group 2

group (getting 7 to 9 or more hours of sleep) is 3.58. The respondents hours of sleep in

either group does not encourage or discourage the respondents GPA. The other results

were; t-value=1.83, df=860, and p-value=0.67. The p-value of the t-test records no

significant relationship between group means.

Table 4 shows the mean GPA while comparing the results of the DV, and KIV

between groups which measures 0.011 represents a significant difference. The Scheffe

test shows there is a GPA difference between the people in Group 1 who get 5 hours of

sleep and those in Group 2 who get 7 hours of sleep.

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Table 4
Results of the ANOVA Comparing Means of the Grade Point Average by

the R Hours Sleep

Sum of
Squares

df Mean
Square

F Sig.

Between
Groups 48.267 5 9.654 2.977 0.011

Within Groups 2775.817 856 3.243
Total 2824.08 861

Table 5 shows, the correlation to be statistically significant, yet inconsistent with

the hypothesis that the numbers of hours sleep has an inverse impact on the DV.

Variables that have significant yet small direct relationships with the DV is the

respondents: head(s) of household highest level of education, on/off campus living

situation, if respondent experienced trouble sleeping, and the number of hours the

respondent works per week.

Table 5
Matrix Correlation Coefficients Resulting from the

Intercorrelation of the Variables in Study

Variables

2

3

4

5

6

7

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1 Grade Point Average .0587 -.0211 .1534 00263 -.0398 .1794 -.0218
2 Number of hours of sleep R gets on a
average night -.0249 .033 -.0074 -.1494 .0953 .0007

3 Type of high school R attended -.0427 .0253 .0088 -.0305 -.0015
4 Highest level of education of R’s family
household head -.0676 .0008 .0076 -.0243
5 Whether R live on-campus or off-
campus .0179 -.0641 -.2684

6 Trouble sleeping -.0821 -.0186
7 Number of hours per week studying -.0032
8 Number of hours per week working
for an employer

*Coefficients that are statistically significant are in bold. Range in Number of cases: 2 to 8.

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Table 6 shows, the coefficient are statistically significant but inconsistent with the

hypothesis. . This table reveals respondents; hours of study, hours of work, trouble

sleeping and the head of household highest level of education have significant effects on

the DV and the type of high school, and number hours of sleep don’t, this also helps to

understand the multiple R and R square relations. In comparing the standardized

coefficients, if they were to be ordered the KIV would be the very last determinant of the

DV.

Table 6
Results of the Regressions of Grade Point Average

on a Model Composed of Sleep Hours, High School, Family Education, Residency,
Trouble Sleeping, Study Hours, and Work Hours

Variables In Model
Unstandardized

Coefficients
Standardized
Coefficients

Number of hours per week studying 0.342 0.176
Number of hours per week working for an employer -0.014 -0.011
Trouble sleeping -0.069 -0.018
Type of high school R attended -0.084 -0.019
Whether R live on-campus or off-campus 0.212 0.058
Highest level of education of R’s family household
head 0.420 0.181

Number of hours of sleep R gets on a average night 0.008 0.005
(Constant) 2.062
Multiple R 0.626
Multiple R Square .392
Number 734

*Coefficients that are statistically significant are in bold.

Notes: Predictors (constant) number hours of sleep R gets on an average night.

Conclusions

The findings presented under the six statistical procedures all reject the

hypothesis. The variables are not related to each other in the 2008 fall study conducted on

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the campus of Howard University. While a student’s GPA may be affected by several

factors however in this case the hours of sleep one engages is not a significant factor. In

this case the respondent’s classification, parents education, residency, trouble sleeping,

hours of study, and high school privatization were all considered and yet the table shows

the hypothesis to be overthrown. This implies it is not necessary for people to focus on

the hours of sleep they get but on the hours of study they engage in at an academic

institution of high learning.

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REFERENCES

i Zager, A., Andersen, M. L., Ruiz, F. S., Antunes, I. B., & Tufik, S. (2007). Effects of acute and chronic
sleep loss on immune modulation of rats [Electronic version]. Regulatory, Integrative and Comparative
Physiology, 293, R504-R509.
ii Schutt, Russell K. Investigating the social world: the process and practice of research. 5th ed. P. 152
iii Schutt, Russell K. Investigating the social world: the process and practice of research. 5th ed. P. 154