1. Math 1040 Group 7 Term Project Fall 2012
Darin Critchlow
Jennifer Farnsworth
Katherine Heller
Monica MacDonald
Heather Oveson
Tatiana Podchinenova
Tatiana Podchinenova

2. Research Question:
For students of different universities: Is amount of hours working related to amount of hours studying per credit hour?
Tatiana Podchinenova

3. Study Design Research question:
“For students of different schools, is amount of hours working related to amount of hours studying per credit hour?”
We attend the school that we decided to obtain data from and go to a place that sees a high amount of student traffic like the student center or the library (a place where there are different and almost random sample of students could be found).
Sampling was to be systematic.
We started on the third person that we say and asked every 10th student that walks in.
We did not use the internet or our classmates.
The sample was to be at least 60 students total, 10 students per each group member. The students were to be different races, genders, and ages.
All students were to be at SLCC, BYU, the U of U, and University of Jordan.
Katherine Heller

4. Data 62 Students Surveyed#
hours working
credit hours
hours studying
hours studuing per credit hour 1 15 17 20
1.18 22 40 4 3
1.33 43 25
1.67 2 16
1.25 23 10 12 8
0.67 44 6 5
0.33 28 13
1.92 24
0.83 45 18 14
3.5
0.4 46
0.2 9
0.44 26
0.6 47 27
0.5 48 7 30
3.33 49
0.53 19
1.05 29
0.77 50 51 11
0.73 35
1.11 31 52 32
0.63 53 33
2.5 54
1.54 34 55
0.71 56
0.75 36 57 37 58
0.875 38 59
6.5
0.54
0.22 39 60
0.56 61
1.17 41 62 21 42
Tatiana Podchinenova

5. Interpretation of Collected Data
We each surveyed about 10 students, for a total of 62 students, and then combined all data into one table.
We calculated the five number summary for each variable, mean, standard deviation, range, mode and outliers.
Using the data collected, we created two boxplots for each of the variables, two histograms and a correlation graph.
The most amount of hours worked was 50 and the least was 0. The most amount of hours studying per credit hour was 0.2 and the least was 3.5 hours.
Tatiana Podchinenova

6. Statistics for Hours Working Column n Mean Variance Std. Dev. Std.
Err.
Median
Data: 62
16.5
Range
Min
Max Q1 Q3
Mode
Outliers 50 40
None
Katherine Heller

7. Histogram
Katherine Heller

8. Boxplot
Katherine Heller

9. Hours Studying per Credit Hour
Statistics for
Hours Studying per Credit Hour
Column n
Mean
Std. Dev.
Median
Mode
Data: 62
1.198
0.778
1.08
1.67
Range
Min
Max Q1 Q3
Outliers
3.3
0.2
3.5
0.67
1.67
3.33, 3.5
Jennifer Farnsworth

10. Histogram
Jennifer Farnsworth

11. Boxplot
Darin Critchlow

12. Statistics for Correlation
Correlation Coefficient
Equation for Line of Regression r=
y= x+1.245
Jennifer Farnsworth

13. Scatterplot
Monica Macdonald

14. Interpretation of Correlation Graph and Analysis
Analysis The shape of each distribution was very irregular, and there was no correlation between the two variables. The value of r was very close to zero( ), while the critical value for our sample size was 0.25.
Interpretation and Conclusions I believe we answered our original question. For the question, “For college students, is number of hours per week working related to number of hours per credit hour spent studying?” the answer is no. From this conclusion, we might infer that there are other variables— difficulty of classes, student motivation, reasons for being in college, etc.—that will affect weekly study time more than the hours of work. I believe our sample accurately reflects the population because of the number of universities we sampled from, and the fact that we included every type of student— traditional, non-traditional, full-time, part-time, unemployed and employed. If I were to repeat the project, I might narrow the population to see if there was more correlation between the two variables. For example, I would change the research question to “For college students who are employed and are taking 9 or more credit hours, is number of hours worked related to time spent studying”
Heather Oveson