Does time spent on Facebook affect your

grades?

Study results presented by: Mary Vietti : Power Point CreatorJustin Price : Editor & Conclusion

Jacob Clayton: Lurking & Confounding VariablesAlyssa Schocker : Difficulties & Surprise Encounters

Jessica Brier : Analysis & Conclusion ContributorAll Team Members Contributed to Data Collection

Study question & design

This observational, cross sectional study was constructed to answer the question of whether time spent on Facebook is related to a student's grade point average.

• The study design attempted to gather information that would be representative of college students in the Salt Lake City area. The sample includes 115 students. To introduce randomness, the data was collected from different college campuses at different times of day. Each student was asked, "What is your GPA? And then, "How many hours do you spend on Facebook each week?" Data was also collected on age and sex of the subject.

Variables Defined

The number of experimental units was determined by the feasibility of time and access to the students by the study designers.

The explanatory variable is the hours spent on Facebook weekly and the response variable is GPA. The Facebook variable data will grouped in classes with a width of 3, so the lowest class limit starts at 3 and ascends by 3 to the last class named 150.

The GPA variable will be grouped into 9 classes. Each spans 25/100th's of a point on a GPA scale that ranges from 1.0 to 4.0. The lowest class starts with data set 1.76 through 2.0, then ascends with each following upper class limit as follows; 2.25, 2.5, 2.75, 3.0, 3.25, 3.5, 3.75, and finally 4.0.

EXPLANATORY VARIABLE

The Explanatory variable is “Hours Spent on Facebook Weekly”. The mean time for the 115 subjects was 8.4 hours per week. The histogram is skewed to the right. This reflects the fact that more students spend few hours on Facebook than spend many hours. In fact, most students spend an hour or fewer a day on Facebook. Therefor, the median value of 5 is probably a better measure of the central tendency. The mode of 7 was the most frequent answer which is the same as 1 hour a day. The standard deviation is quite large: 15.88 which, as you will see, is related to the outliers in the data described below.

n=115 subjects, Mean=8.4 hours, Median=5 hours, Mode 7 hours, standard deviation 15.88 hours

Frequency Histogram

Hours Spent on Facebook Weekly

Box Plot GraphTime spent on Facebook Weekly

X XX [ -- -------]XX X X X X X X X

I---------I--------I-------I---------I--------I--------I--------I--------I--------I---------I--------I-------I-15 0 15 30 45 60 75 90 105 120 135 150 165

The box plot shows that 50% of the data is between the 2 and 8.5. The interquartile range is 6.5 around a median value of 5.0. The lower fence is -7.75 and the upper fence is 18.25. The outliers include any subject who spent greater than 18.25 hours a week. The lower fence was -7.75 which is lower than the lowest possible data value of 0. This leaves 12 outliers which is 10.4% of the data collected.

RESPONSE VARIABLE

The response variable is the subject’s “Grade Point Average, GPA”. The histogram appears skewed to the left. This reflects the fact that the students surveyed have good grades. Here, the median value of 3.5, the mean of 3.46 and the mode of 3.5 are all probably good measures of the central tendency. This is supported by the small standard deviation of .041. All the data is within a small range; see the box plot graph.

n=115 subjects, Mean GPA=3.46, Median GPA=3.5, Mode GPA=3.5, standard deviation 0.041

FREQUENCY HISTOGRAMGrade Point Average

Box Plot GraphGrade Point Averages

x x [----------------------------- -------- ] I--------I--------I--------I--------I--------I--------I--------I--------I--------I--------I---------I

0 2 2.25 2.5 2.75 3 3.25 3.5 3.75 4 4.5 4.75

The box plot shows that 50% of the data is between 3.2 and 3.8. Therefore the interquartile range is 0.6 around a median value of 3.5. The lower fence is 2.3 and the upper fence is 4.7. The outliers include any subject who’s GPA is less than 2.3. The upper fence is 4.7 which is higher than the highest possible data value of 4.0. This leaves 2 outliers which is 1.7% of the data collected.

CORRELATING THE DATAThe data does not have a strong linear correlation. The Linear Correlation Coefficient was -0.048, which indicates a weak inverse relationship between the variables. The Line of regression is as follows:

GPA per Facebook Hours

X Axis: Hours Spent On Facebook Per Week Mean: 8.456 Standard Deviation: 15.876

Y Axis: Grade Point Average Mean: 3.455 Standard Deviation: 0.415 Line of Regression: Y = -0.0012X + 3.466

Correlation Coefficient: -0.0481 Y intercept: 3.466 Slope: -.0012

Although a line of regression has been applied here to this data, the linear correlation does not meet the criteria imposed by a critical value. The 95% Critical Value for a sample size of 100 or more is 0.195; as listed in the online textbook, Collaborative Statistics, by B. Illowski, PH.D. and Susan Dean. This critical value allows only 2 degrees of freedom which is an indication that the data might have a linear correlation if given looser parameters.

Difficulties & Surprises Encounters

Gathering the information for this research assignment was particularly easy. We surveyed 115 people and asked how many hours per week they spent on Facebook, and what their GPA was. StatCrunch made what could have been a very difficult task, pretty easy. We were able to make all of the graphs and tables using this program. It was also a very good review for the things we had learned previously in the semester. We were surprised that there was no correlation between Facebook hours and GPA. In fact, one of the biggest surprises was that some people spent close to 20 hours on Facebook per week, and they were still able to maintain a 4.0.

LURKING & CONFOUNDING VARIABLES

• How much time a student studies• Difficulty of classes• Number of credit hours• What a student does on Facebook

(they could be doing a group report)

• Overall health of student• Jobs• Family Life

Analysis

While the data for GPA appeared to be normally distributed, that for Facebook hours did not. As we have

mentioned, there did not appear to be a significant linear correlation between the two variables. Based on Pearson's table, for a sample size of 115, the absolute value of the correlation coefficient should be greater

than .164 at the 90% level of confidence. The absolute value of our correlation coefficient is 0.0481, which is

less than .164. Therefore, we do not reject our null hypothesis, which is to say that there is not a

statistically significant relationship between GPA and Facebook hours per week.

Interpretation and Conclusions

In conclusion our experiment did not demonstrate a correlation between GPA and Facebook use. As we stated in the Lurking and Confounding Variables there are extenuating circumstances in student’s lives for them not to be above the mean. So to answer our question “Does Time Spent on Facebook Affect Your GPA”, IT DOES NOT!!!