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Investigating the Relationship Between Sleep Quality and Academic Performance in College Students

In this insightful study, we delve into the crucial yet often overlooked connection between sleep quality and the academic performance of college students. We explore the impact of sleep on cognitive functioning and its influence on GPA. Our research utilizes the widely recognized Pittsburgh Sleep Quality Index (PSQI) to assess sleep quality, while self-reported GPA serves as a measure of academic achievement. By delving into the results, we aim to shed light on the potential factors affecting academic success, as well as the significance of addressing sleep quality in the context of higher education.

Problem Description

This statistical analysis assignment delves into the intriguing connection between sleep quality and academic performance among college students. Sleep quality is known to influence cognitive function, and this research endeavors to shed light on its role in determining educational outcomes. To investigate this, we employed the Pittsburgh Sleep Quality Index (PSQI) to gauge sleep quality and self-reported GPA as a measure of academic performance.


Participants: Our research included a cohort of 49 college students, representing diverse ethnic backgrounds and gender identities. The average age of the participants was 25.88 years, with a standard deviation of 7.664.


  • Sleep Quality: We assessed sleep quality using the PSQI, a ten-item questionnaire designed to evaluate various aspects of sleep. To maintain consistency, we recoded the responses on a 0-3 scale.
  • Academic Performance: We measured academic performance using participants' self-reported GPAs.


Reliability Statistics:

Cronbach's Alpha N of Items
.779 10

Table 1: Reliability statistics

We evaluated the internal consistency of our assessment tools using Cronbach's alpha, a measure of how well items within a scale or questionnaire correlate. The calculated Cronbach's alpha coefficient was 0.779, indicating good internal consistency for the sleep quality assessment. Generally, an alpha value above 0.7 is considered acceptable for research, and above 0.8 is considered good. Thus, our scale exhibited satisfactory internal consistency, suggesting that the items collectively measured the construct of interest, sleep quality, in a reasonably reliable manner.

Please answer the following questions. Chose the ones that fits your description

Frequency Percent Valid Percent Cumulative Percent
Valid Sophomore 2 4.1 4.1
Junior 11 22.4 22.4
Senior 36 73.5 73.5
Total 49 100.0 100.0

Table 2: Descriptive statistics

What is your ethnicity?

Frequency Percent Valid Percent Cumulative Percent
Valid White 25 51.0 51.0
Black or African American 8 16.3 16.3
American Indian or Alaska Native 1 2.0 2.0
Asian 2 4.1 4.1
Native Hawaiian or Pacific Islander 1 2.0 2.0
Other 12 24.5 24.5
Total 49 100.0 100.0

Table 2: Ethnicity percentages

Which term best describes your gender identity?

Frequency Percent Valid Percent Cumulative Percent
Valid Male 10 20.4 20.4
Female 35 71.4 71.4
Non-binary / third gender 3 6.1 6.1
Prefer not to say 1 2.0 2.0
Total 49 100.0 100.0

Table 3: Percentages for gender identity

Our sample comprised 49 participants, with an average age of 25.88 years and a standard deviation of 7.664. The majority identified as seniors (73.5%), followed by juniors (22.4%) and sophomores (4.1%). Regarding ethnicity, the largest group was White (51.0%), followed by Black or African American (16.3%) and Other (24.5%). In terms of gender identity, most participants identified as female (71.4%), while 20.4% identified as male, 6.1% as non-binary/third gender, and 2.0% preferred not to say. The mean sleep quality score (PSQI-Total) was 12.31 (SD = 5.966) on a 0-30 scale, and the GPA mean was 3.212 (SD = 0.148) on a 4.0 scale.

Correlation Analysis:


PSQI_TOTAL What is your GPA?
PSQI_TOTAL Pearson Correlation 1 -.064
Sig. (1-tailed) .330
N 49 49
What is your GPA? Pearson Correlation -.064 1
Sig. (1-tailed) .330
N 49 49

Table 4: Correlation analysis

We assessed the relationship between sleep quality (PSQI-Total) and GPA, finding a weak negative correlation with a Pearson correlation coefficient of -0.064 (p = 0.330). This suggests that lower sleep quality is associated with slightly lower academic performance, although this relationship was not statistically significant.

Regression Analysis:

Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate
1 .064a .004 -.017 .447
2 .294b .086 .047 .433

Table 5: Model summary for the regression analysis


Model Sum of Squares df Mean Square F Sig.
1 Regression .039 1 .039 .195 .661b
Residual 9.392 47 .200
Total 9.431 48
2 Regression .815 2 .408 2.176 .125c
Residual 8.615 46 .187
Total 9.431 48

Table 6: ANOVA Results


Model Unstandardized B Coefficients Standard error Standardized Coefficients Beta t Sig.
B Std. Error Beta
1 (Constant) 3.212 .148 21.757 .000
PSQI_TOTAL -.005 .011 -.064 -.442 .661
2 (Constant) 3.365 .162 20.825 .000
PSQI_TOTAL -.004 .010 -.059 -.421 .676

Table 7: Coefficients

Two regression models were examined to predict GPA based on sleep quality (PSQI-Total) and ethnicity. Neither model showed a significant relationship between sleep quality and GPA. In the first model (PSQI-Total only), the unstandardized coefficient for PSQI-Total was -0.005 (p = 0.661). In the second model (PSQI-Total and ethnicity), the coefficient for PSQI-Total was -0.004 (p = 0.676), indicating that sleep quality did not significantly predict GPA. However, the ethnicity variable in the second model exhibited a significant negative relationship with GPA (β = -0.287, p = 0.048), suggesting that students from certain ethnic backgrounds might have lower GPAs.


This study explored the relationship between sleep quality and academic performance among college students. While we observed a weak negative correlation between sleep quality and GPA, it was not statistically significant, possibly due to factors like the relatively small sample size and unaccounted confounding variables. Regression analysis also revealed that sleep quality alone may not be the sole determinant of academic performance, suggesting the presence of other influencing factors, such as study habits, stress levels, and individual characteristics.

Notably, the ethnicity variable emerged as a significant factor affecting GPA, highlighting potential disparities among students of various ethnic backgrounds. It's crucial to acknowledge that ethnicity can intersect with socio-cultural factors, impacting academic performance. Further research is needed to delve into the mechanisms behind these disparities.


In conclusion, this study explored the link between sleep quality and academic performance in college students. Although we found a weak negative correlation between sleep quality and GPA, it was not statistically significant. Sleep quality alone did not emerge as a significant predictor of academic performance. However, we observed a significant relationship between ethnicity and GPA. These findings should be interpreted cautiously, considering limitations such as a small sample size and self-reported measures. Future research with larger and more diverse samples, along with objective assessments of sleep quality and other potential influencing variables, is essential for a more comprehensive understanding of this relationship.