NO time to study

1. NO time to study By: Nick Hall Andrew Kalfayan Michael Laow Joey Suitonu

2. Mission Statement • Could the lack of time due to increasing work hours be the cause of lower academic performance? • Is there a significant difference in GPA from the sample of employed and unemployed students surveyed? • Our goal was to determine whether it is beneficial to work less or not at all while attending school.

3. Hypothesis • Everyday college students have to balance their lives between school and work. With today’s cost of living, especially in Southern California, individuals have to work more hours to maintain their lifestyles. • Our belief is that there is a correlation between the employed and unemployed students and their overall G.P.A.

4. The Survey “No Time to Study” Male Female Age: Class Standing : Freshman Sophomore Junior Senior GPA : 1.5 – 1.9 2-2.24 2.25-2.49 2.5-2.74 2.75-2.99 3- 3.24 3.25-3.49 3.5- 3.74 3.75-4 How many hours do you work in one week?  Do you schedule your class schedule around work? Do you schedule your work around your class schedule?  How many hours do you study outside of class per week? What is your major? On average, how many hours of sleep do you get per night?   How many units are you currently taking? Would you be willing to compromise work hours for study hours?  Thank you very much for your time.

5. Survey Scope • Southern California Cal State Universities • Our main focus was on the College of Business at California State University San Marcos • We also received data from an assortment of different majors such as Kinesiology, Communications, Human Development, Psychology, Biology, Criminology, and Liberal studies, and Cosmetology. • Given that our objective was focused on work hours and its effect on GPA the differences in each major was not an issue.

6. Class Standing

7. Age Scope

8. GPA Range

9. Correlation between Hours Studied and GPA

10. GPA to Hours Worked

11. Employed vs. Unemployed Employed Mean/GPA: 3.096106 Standard Deviation:0.473147 Sample size: 113 Unemployed Mean/GPA: 3.326786 Standard Deviation: 0.49723 Sample size: 28 There is a significant difference in GPA when comparing employed and unemployed students.

12. t Test for Differences in Two Means Sample 1: GPA (non employed) Sample 2: GPA (employed) Attempted to find a difference greater than 0. Result: t-value was greater than upper critical value making us reject the null hypothesis.

13. Employed Students’ Schedules “Students class schedule around work” Mean/GPA 3.027157 STDEV 0.442051 Sample size 51 “Work schedule around class” Mean/GPA 3.152823 STDEV 0.49358 Sample size 62

14. Compromise Answered “Yes” Mean/GPA 3.075641 STDEV 0.505254 Sample size 78 Answered “No” Mean/GPA 3.142353 STDEV 0.395231 Sample size 35

15. Correlation Test Boxes marked in yellow show greater, yet not significant, correlations with the variables being compared. It seems, as though, Sleep and work hours/week have a negative correlation and hours studied outside of class might have a positive impact on GPA.

16. Regression Analysis

17. Regression analysis less high p values

18. t Test for Differences in Two Means Sample 1: GPA (non employed) Sample 2: GPA (employed) Attempted to find a difference greater than 0. Result: t-value was greater than upper critical value making us reject the null hypothesis.

19. A Logical Explanation of Cause for Difference in GPA Analyzed and observed: -The difference in hours studied per week between employed and unemployed students -The difference in hours of sleep per night between employed and unemployed students

20. Surprising Results Sleep difference (per night) Unemployed 7.339286 Employed 6.626106 Extra sleep for unemployed 0.71318 ~42.79077118 minutes *Difference in GPA: Unemployed +0.23 Study hour difference Average hours studied for Unemployed 9.857143 Employed 10.46903 Difference in hours studied 0.611884~36.71302 minutes a week

21. Explanation • With employed students studying longer per week than unemployed students, but sleeping around 45 minutes less per night, we believe that their studying is being done at the expense of their sleep. • Unemployed students have the privilege of a higher probability of studying in the day while employed students are working.

22. Assumption • Studies have shown that studying in the day proves to be more effective than studying through the night. Employed students: -study for more hours but are losing sleep due to their late night studying Result: -lower GPA due to lower functioning and study habits that prove to be detrimental when compared to unemployed students.

23. Conclusion/Assumption • After extensive research and data analysis, as a group, we believe that employed students have, on average, a lower GPA than unemployed students. • Our correlation and regression analysis doesn’t clearly distinguish the reason for the lower GPA among employed students, yet it shows that some independent variables are more significant than others.

24. Recommendation • We recommend that employed students cut down there work hours as much as possible to help gain more study hours during the day. • This will help employed students retain information quicker when studying and invest more time into their sleep.

25. Errors in Survey How many hours do you study outside of class per week? Correction: How many hours do you study outside of class per week? -and- At what time of day do you usually study?