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Created: Oct 11, 2012
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Georgia College Campus Involvement Research Project (Wombats)
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Is there a correlation between a student's level of involvement on Georgia College's campus and the number of weekends they leave the Milledgeville area on the weekends?


Lindsey Harrison 

Mary Ashley Gibson

Kelsey Richardson

Kelsey Stone

Katie Garrett


As Georgia College student's we thought it would be interesting if see if there is a correlation between the level of involvement a student has and how often they leave the Milledgeville community on the weekends. Georgia College is often referred to as a "suitcase-college" meaning students frequently leave the campus on the weekends. These results could be beneficial to various organizations on campus such as CAB, Students Affairs, and Georgia College Admissions Office. 

 The population for our survey was Georgia College students. Our sample size was 75 students ranging from freshman to seniors at Georgia College. We believe there is a moderately negative correlation because the more involved a student is on campus the less they will go home; however, there are other variables that could influence this greatly. Our two main research variables are level of involvement on campus and the frequency a student leaves the Milledgeville community on the weekends. Our demographic variables are class year, gender, place of residence in Milledgeville, and how far away a student's family lives. 


     We collected data by conducting a random sample survey at Georgia College's fountain. Our survey was on paper with a series of circled answers. The fountain is a central location on campus which attempted to reduce bias. Our survey was composed of two main variables of interest and several demographic variables. The construct was designed to measure the overall involvement per student on Georgia College's campus. The student's were asked to estimate the amount of time per week they devote to orgainizations including honor societies, greek life, student organizations, intramurals, religious groups, and job / internships. A descriptive summary for our two main variables is listed below. 


Two Main Variable Results

Result 1: Descriptive Statistics for 2 Main Variables   [Info]
Summary statistics:
Column n Mean Variance Std. Dev. Std. Err. Median Range Min Max Q1 Q3
GC Involvement 75 8.4 3.5405405 1.8816324 0.21727219 8 7 6 13 7 10
# Weekends Gone 75 1.88 1.4043243 1.1850419 0.13683686 2 5 0 5 1 2

Result 2: Frequency Table for 2 Main Variables   [Info]
Frequency table results for # Weekends Gone:
# Weekends Gone Frequency Relative Frequency
0 2 0.026666667
1 35 0.46666667
2 20 0.26666668
3 10 0.13333334
4 4 0.053333335
5 4 0.053333335

Result 3: Relative Frequency Histogram for Weekends Gone   [Info]
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Result 4: Frequency Table for GC Involvement   [Info]
Frequency table results for GC Involvement:
GC Involvement Frequency Relative Frequency
6 14 0.18666667
7 13 0.17333333
8 17 0.22666667
9 9 0.12
10 12 0.16
11 3 0.04
12 6 0.08
13 1 0.013333334

Result 5: Relative Frequency Histogram for Level of Campus Involvement   [Info]
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Result 6: Regression Equation / Scatter Plot for 2 Main Variables   [Info]
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Result 7: Simple Linear Regression for 2 Main Variables   [Info]
Simple linear regression results:
Dependent Variable: # Weekends Gone
Independent Variable: GC Involvement
# Weekends Gone = 2.9187787 - 0.123664126 GC Involvement
Sample size: 75
R (correlation coefficient) = -0.1964
R-sq = 0.03855579
Estimate of error standard deviation: 1.1699039

Parameter estimates:
Parameter Estimate Std. Err. Alternative DF T-Stat P-Value
Intercept 2.9187787 0.62197345 ≠ 0 73 4.6927705 <0.0001
Slope -0.123664126 0.072276905 ≠ 0 73 -1.7109771 0.0913

Analysis of variance table for regression model:
Source DF SS MS F-stat P-value
Model 1 4.0067177 4.0067177 2.9274423 0.0913
Error 73 99.913284 1.3686751
Total 74 103.92

 Our regression equation for our two main variables is y=2.919-0.124x where y is the number of weekends a student leaves Milledgeville and x is the level of involvement of campus determined from our construct.  The slope is -0.124. The interpretation of this is that with every point increase on our construct in campus involvement a student has, the number of weekends that students will go home decreases by 0.124. The y-interept for our regression equation is 2.919. However, this does not have any relevance to our particular  survey because the lowest anybody can score on from our campus involvement construct is a 6. From our regression equation if a person is not involved at all, and therefore scores a 6, then the estimated number of weekends they will go home is about 2.165.

 The strength of our regression equation is determined by the correlation coefficient. Our value r=-0.196 shows that there is a negative relation between campus involvement and weekends gone from Milledgeville, but because the number is so small there is hardly any correlation at all. We conclude that there is an extremely weak negative correlation. Our value of r-squared=0.039 means that about 3.9% of the data is explained by our regression equation. 

When exploring our data grouped by our demographic variables we noticed a strong difference between females and males, whose scatter plot is shown below. The regression equation for the females is given by y=3.644-0.191x with r=-0.269 and r-squared=0.072. The regression equation for the males is given by y=1.878-0.029x with r=-0.061 and r-squared=0.004. There is a stronger correlation between level of GC involvement and number of weekends gone for females than males because the correlation coefficient is closer to -1 for the females than for the males. 

Result 8: Scatter Plot by Gender   [Info]
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 Demographic Variable Results

Result 9: Student's Distance from Home Histogram   [Info]
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Result 10: Class Hours Histogram   [Info]
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Result 11: Class Year Pie Chart   [Info]
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Result 12: Residence Pie Chart   [Info]
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Result 13: Gender Pie Chart   [Info]
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When planning this research study we expected there to be a strong negative correlation between the level of involvement on GC campus and the number of weekends a student typically leaves the Milledgeville area a month. What we actually discovered is that although there is a negative correlation it is an extremely weak one. When we grouped the scatter plot by gender the correlation was slightly better for females than our original scatter plot, but it would still be considered a weak correlation. Our population goal was to represent all Georgia College students; however, when looking at our demographic variables in graphical form it is easy to notice that not all class years were represented fairly. We have more sophomores and hardly any seniors at all. One mistake we made was to underestimate the potential for lurking variables. There are countless reasons for a student to leave the Milledgeville area on the weekends that we did not take into account. The student's home life is one lurking variable or if he/she has a significant other who goes to a different school. These are all factors that could influence a student's decision to leave Milledgeville which were not considered in our study. For our study to be more beneficial we could ask why and/or where they are leaving to on the weekends. 

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<A href="">Georgia College Campus Involvement Research Project (Wombats)</A>

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