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Analyzing Marineford

Submitted by drosen on Fri, 03/09/2018 - 14:24


Our group (#2) chose to focus on the hours slept and hours studied in relation to GPA. We determined that making 2 graphs showing the gradual change in GPA with both hours slept as well as hours studied would change the average GPA per student, regardless of gender. The independent variables in these graphs would be either the hours slept or the hours studied.  Upon analyzing the data we suspect that the hours spent studying, nor the hours one spent sleeping are significntly correlated to the GPA of the students. We could do this by comparing the overall graphs or the averages of 2 distinct groups such as the top 10 and the bottom 10 students. In addition, we could also create a normal distribution of the data and establish a standard deviation from the class average. From there, we could determine who are outliers and then assess their hours slept and studied to see if there are any obvious differences that may have led to this variability.