Activestats

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Summary of findings and preliminary conclusions: The problem I’m trying to solve is : Universities and colleges do not like to admit students who do not perform well. It is expensive and unpleasant for both the student and the school. Since I work in the Department of Education and I’m a trained statistician, my supervisor has asked that I assist the Head of the Admissions Department. I have been given the MIDWEST SCHOLASTIC DATA file to develop a detailed statistical plan that the Admissions Officer can use to determine which students are most successful at her university. 13 variables are considered for each student: sex (SEX), high school percentile (HSP), cumulative GPA (GPA), age (AGE), total credits earned (CREDITS), classification (CLASS), school/college (COLLEGE), primary major (MAJOR), residency (RESIDENCY), admission type (TYPE), ACT English score (ENGLISH), ACT math score (MATH), and ACT composition score(COMP). To conclude what I observe on the project parts B and C, is that there are 860 students, which 60.7% are female and 39.3% are male The AGE and CREDITS are related, because they have a correlation of 0.722, which is strong. The HSP and GPA are also related, with a correlation 0.515, which is moderate. CREDITS and GPA have a moderated correlation of 0.193. ENGLISH and COMP are apparently related with a correlation of 0.812 which is strong, and ENGLISH and MATH are also related with a correlation of 0.455 which is moderate. MATH and COMP are also related with a correlation of 0.730 which is strong. Thus, students that did well in high school with HSP bigger than 74% and with ACT scores higher than 23.5 and that also did well in college with GPA higher than 3.0 and have 71 credits or more should be consider to be successful at the university . What is a good predictor of GPA?

Methods: use the data provided to find correlations between between several factors and the GPA of students at Midwest such as: where do they live, how old are they,...
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