The following report is an analysis of the Performance data set, which looked at the study habits, extracurricular, test scores and overall academic evaluation of 10000 students. This report will break down the data and examine it as well as create models to better predict a student’s overall Academic Performance.
The table contained the following 6 attributes which were renamed, Hours Studied (Study.Hrs), Previous Scores (Tests), Extracurricular Activities (Activities), Sleep Hours (Sleep.Hrs), Sample Question Papers Practiced (Practice.Tests) and Performance Index (Academics). In addition to these name modifications another category was created to see the difference between Tests and Academics. Lastly, the following categorical variables were created from to bin the values.
Study.Hrs derived Study.Quality where “Low”=[1,3], “Med”=[4,6] and “High”=[7,9].
Tests derived Test.Letter where “A+”=[90,100], “A”=[80,89], “B”=[70,79],“C”=[60,69], “D”=[50,59] and “F”=[0,49].
Sleep.Qual was derived from Sleep.Hrs where “Low”=[4,5], Med=[6,7], High[8,9].
Test.Prep was derived from Practice.Tests where “Low”=[0,2], “Med”=[3,6] and “High”=[7,9].
Total.Letter was derived from Academics where “A+”=[90,100], “A”=[80,89], “B”=[70,79],“C”=[60,69], “D”=[50,59] and “F”=[0,49]. Activities.1 was created as a binary attribute. This gave the following structure
## Study.Hrs Tests Activities Sleep.Hrs Practice.Test Academics Score.Difference
## 1 7 99 Yes 9 1 91 8
## 2 4 82 No 4 2 65 17
## 3 8 51 Yes 7 2 45 6
## 4 5 52 Yes 5 2 36 16
## 5 7 75 No 8 5 66 9
## 6 3 78 No 9 6 61 17
## Study.Quality Test.Grade Sleep.Qual Test.Prep Total.Letter Activities.1
## 1 High A+ High Low A+ 1
## 2 Med A Low Low C 0
## 3 High D Med Low F 1
## 4 Med D Low Low F 1
## 5 High B High Med C 0
## 6 Low B High Med C 0
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