Transcript NO time to study

By:
Nick Hall
Andrew Kalfayan
Michael Laow
Joey Suitonu



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.


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.
“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.
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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.
Freshman
Sophomore
Junior
3% 4%
33%
60%
Senior
Age
35
30
# of People
25
20
15
Age
10
5
0
18
19
20
21
22
23
24
25
26
27
Age
28
29
30
31
32
35
36
47
35
30
# of students
25
20
GPA
15
10
5
0
2-2.24
2.25-2.49
2.5-2.74
2.75-2.99
3-3.24
GPA Range
3.25-3.49
3.5-3.74
3.75-4
4
y = 0.0155x + 2.9818
R² = 0.0356
3.8
3.6
3.4
3.2
3
Linear (Series1)
2.8
2.6
2.4
2.2
2
0
5
10
15
20
25
30
35
40
GPA to Hours Worked
y = -0.0016x + 3.1363
R² = 0.001
4
3.8
3.6
3.4
GPA
3.2
Series1
3
Linear (Series1)
2.8
Linear (Series1)
2.6
2.4
2.2
2
0
10
20
30
Hours Worked
40
50
60
Employed
Unemployed
Mean/GPA:
Mean/GPA:
3.096106
3.326786
Standard Deviation:
Standard Deviation:
0.473147
Sample size:
113
0.49723
Sample size:
28
There is a significant difference in GPA when comparing
employed and unemployed students.
t Test for Differences in Two Means
Data
Hypothesized Difference
Level of Significance
Population 1 Sample
Sample Size
Sample Mean
Sample Standard Deviation
Population 2 Sample
Sample Size
Sample Mean
Sample Standard Deviation
0
0.05
28
3.327
0.32
113
3.09
0.6
Intermediate Calculations
Population 1 Sample Degrees of Freedom
27
Population 2 Sample Degrees of Freedom
112
Total Degrees of Freedom
139
Pooled Variance
0.309963
Difference in Sample Means
0.237
t Test Statistic
2.016519
Upper-Tail Test
Upper Critical Value
p -Value
Reject the null hypothesis
1.65589
0.022836
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.
“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
Answered “Yes”
Mean/GPA
3.075641
STDEV
0.505254
Sample size
78
Answered “No”
Mean/GPA
3.142353
STDEV
0.395231
Sample size
35
GPA
GPA
work hours/week
hours studied outside of class
sleep
units
1
-0.031227515
0.263325396
-0.063688945
0.195108963
work hours/week hours studied outside of class
1
-0.029504486
-0.328935603
-0.11585094
sleep
units
1
-0.193046725
1
0.17818498 -0.147778365
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.
1
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
0.303429093
0.092069215
0.058442148
0.45911311
113
ANOVA
df
Regression
Residual
Total
Intercept
work hours/week
hours studied outside of class
sleep
units
SS
2.308473211
22.76476351
25.07323673
MS
0.577118303
0.210784847
Coefficients Standard Error
2.548873967
0.447838104
-0.000286653
0.004986726
0.018619854
0.007468639
0.00105703
0.040130681
0.026300942
0.016380126
t Stat
5.691507587
-0.057483247
2.493071776
0.026339708
1.605661815
4
108
112
F
Significance F
2.73795 0.032430137
P-value
Lower 95% Upper 95%Lower 95.0%
Upper 95.0%
1.09E-07 1.661181179 3.436567 1.661181 3.436567
0.954266 -0.010171208 0.009598 -0.01017 0.009598
0.014182 0.003815715 0.033424 0.003816 0.033424
0.979035 -0.07848894 0.080603 -0.07849 0.080603
0.111268 -0.006167308 0.058769 -0.00617 0.058769
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.303348
R Square
0.09202
Adjusted R Square
0.075511
Standard Error
0.454933
Observations 113
ANOVA
df
Regression
Residual
Total
SS
MS
2 2.307242 1.153621
110 22.76599 0.206964
112 25.07324
Coefficients
Standard Error t Stat
Intercept 2.548108 0.217478 11.71665
hours studied
0.018588
outside0.007271
of class
2.55661
units
0.026359 0.015902 1.657595
F Significance F
5.57403 0.004945
P-value Lower 95%Upper 95%Lower 95.0%
Upper 95.0%
4.53E-21 2.117119 2.979098 2.117119 2.979098
0.011933 0.004179 0.032996 0.004179 0.032996
0.100249 -0.00515 0.057873 -0.00515 0.057873
t Test for Differences in Two Means
Data
Hypothesized Difference
Level of Significance
Population 1 Sample
Sample Size
Sample Mean
Sample Standard Deviation
Population 2 Sample
Sample Size
Sample Mean
Sample Standard Deviation
0
0.05
28
3.327
0.32
113
3.09
0.6
Intermediate Calculations
Population 1 Sample Degrees of Freedom
27
Population 2 Sample Degrees of Freedom
112
Total Degrees of Freedom
139
Pooled Variance
0.309963
Difference in Sample Means
0.237
t Test Statistic
2.016519
Upper-Tail Test
Upper Critical Value
p -Value
Reject the null hypothesis
1.65589
0.022836
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.
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
Sleep difference (per night)
Study hour difference
Unemployed
7.339286
Employed
6.626106
Extra sleep for unemployed
0.71318 ~42.79077118 minutes
Average hours studied for
Unemployed
9.857143
Employed
10.46903
Difference in hours studied
0.611884~36.71302 minutes a
week
*Difference in GPA:
Unemployed +0.23


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.
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.

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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.


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.
How many hours do you study outside of class
per week?
Correction:
How many hours do you study outside of class
per week?
-andAt what time of day do you usually study?