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Data Analysis


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Variable: ID
    The ID is simply to differentiate one student from another. It categorizes each separate student into a specific number, probably for referencing purposes. Although it uses numbers, this variable is categorical rather than quantitative because it is identifying something—the student—and not measuring it. This data is discrete because each student has an ID that is one whole number that is finite. There can be no outliers and the data cannot be skewed in anyway because this data follows a pattern; each ID number is one greater than the last. This can be seen clearly below. The ID is useful in this study because it can be used to reference each specific student.
Variable: Sex
    Sex categorizes each student into two categories: male or female. It measures the number of girls and the number of boys in this study. This data is discrete because sex is a definitive variable. Because it is definitive, it is categorical rather than quantitative. There are only two categories in this variable so there aren’t any outliers per say, but it can be seen below that the data is skewed—there are significantly more girls in this study than boys. The unit in this data is whether the student is male or female. This variable is important to the study because it can prevent a lack of diversity in the student body. If a college has a significant amount of male students, for example, and very few female students, it might take initiative to accept more females.

 Variable: HSP
    This variable is the high school percentile. It ranks a student by what top percentage the student was in during their high school years. HSP is discrete because a rank is a finite number. It is measured in percentiles. It does not change continuously unless a student is constantly doing worse or doing better by a certain amount, and even then, these students are currently in college and their HSP cannot change. There do not seem to be any significant outliers. This data is quite clearly skewed to the left. HSP can be used in this study as a reference to a student’s improvement. If a student was in the bottom 32% of his or her graduating class but managed to pull off a 3.8 GPA in college, then that student has an aptitude for improvement. At the same time, if a student was in the top 85% of their high school class but only has a 2.0 GPA, that person does not make a good college student.

Variable: GPA
    The GPA is the student’s current grade point average. It measures their overall grade on a 4.0 scale. Because each student has a
Description of the variables: Look at each variable separately. What is the variable measuring? Determine whether it is categorical or quantitative. Is the data discrete or continuous? Are there any outliers in this variable? Is the data skewed or in any way ‘different’? What is the unit of measurement of the variable? What is its importance in this study. 







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