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Created: Feb 17, 2012
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GPA vs. Studying and Extra-curricular activity
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Introduction: Students are constantly faced with multiple things that deserve individual time and attention. Of the variety of appointments and arrangements our group felt that the majority of student activity could fall under two groups: studying and extra-curricular activity. With so many oppurtunities for students to spend their time our group examined the average number of hours a student studies and the average hours of student involvment with extra-curricular activity in comparison with their cumlitive gpa.

 

Our hypothesis is that the ammount of hours studied and hours involved in extra-curricular activities directly correlates with a students  cumlitive gpa. Appropriately, we thought that the more involved in extra-curricular activities a student was the lower their respective gpa would be. We also thought there would be a correlation with studying and overall grades.

 

Methods: We first had to choose out population. Since we would not be able to survey students from multiple schools we decided to limit our tests within Georgia College & State University. The population was also limited to under graduate students (freshman, sophomore, junior, senior). To obtain information we created a survey on www.surveymonkey.com. The site allowed us to anonomyously track which students took the test as well as view individual results. Our survey can be tracked to the link below:

 

http://www.surveymonkey.com/s/KKPYBZV

 

We asked students six questions:

 

1.     How many hours a week are you involved in extra-curricular activity?

2.     How many hours a week do you study

3.     What is your major?

4.     What year are you?

5.     How many hours are you taking this semester?

6.     What is your gpa?   

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wwConclusion: We thought there would be a strong negative correlation between GPA and extra-curricular activities, but when we put our results together we discovered there is very little correlation between any of the two variables. This could be partially due to the fact that our population was not as concentrated as it could have been. We also did not get to survey a large number of students compared with the number of students that go here.

      R-values: 0.4792, 0.2787

   


 

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Result 1: Grade Level Pie chart   [Info]
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Result 2: Extra-curricular activity vs. GPA   [Info]
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Result 3: Simple Linear Regression of Extra-curricular activity   [Info]
Simple linear regression results:
Dependent Variable: Hrs EX/wk
Independent Variable: GPA
Hrs EX/wk = -24.536314 + 10.554199 GPA
Sample size: 30
R (correlation coefficient) = 0.4792
R-sq = 0.22962138
Estimate of error standard deviation: 5.900631

Parameter estimates:
Parameter Estimate Std. Err. Alternative DF T-Stat P-Value
Intercept -24.536314 11.474733 ≠ 0 28 -2.1382906 0.0414
Slope 10.554199 3.6533577 ≠ 0 28 2.8889036 0.0074


Analysis of variance table for regression model:
Source DF SS MS F-stat P-value
Model 1 290.57822 290.57822 8.345765 0.0074
Error 28 974.8885 34.817444
Total 29 1265.4667

Result 4: Extra-curricular plot with line   [Info]
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Result 5: Scatter Plot   [Info]
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Result 6: Simple Linear Regression of studying   [Info]
Simple linear regression results:
Dependent Variable: hrs study/wk
Independent Variable: GPA
hrs study/wk = -17.048279 + 8.617933 GPA
Sample size: 30
R (correlation coefficient) = 0.2787
R-sq = 0.077660546
Estimate of error standard deviation: 9.065162

Parameter estimates:
Parameter Estimate Std. Err. Alternative DF T-Stat P-Value
Intercept -17.048279 17.628675 ≠ 0 28 -0.96707654 0.3418
Slope 8.617933 5.612667 ≠ 0 28 1.5354435 0.1359


Analysis of variance table for regression model:
Source DF SS MS F-stat P-value
Model 1 193.73976 193.73976 2.3575869 0.1359
Error 28 2300.9602 82.177155
Total 29 2494.7

Result 7: Scatter Plot of studying with line   [Info]
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Data set 1. gpa vs. extra   [Info]
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