Part 5 - Explore Data
Let’s take a look at the data frame…
## school sex age address famsize Pstatus Medu Fedu Mjob Fjob reason
## 1 GP F 18 U GT3 A 4 4 at_home teacher course
## 2 GP F 17 U GT3 T 1 1 at_home other course
## 3 GP F 15 U LE3 T 1 1 at_home other other
## 4 GP F 15 U GT3 T 4 2 health services home
## 5 GP F 16 U GT3 T 3 3 other other home
## 6 GP M 16 U LE3 T 4 3 services other reputation
## guardian traveltime studytime failures schoolsup famsup paid activities
## 1 mother 2 2 0 yes no no no
## 2 father 1 2 0 no yes no no
## 3 mother 1 2 3 yes no yes no
## 4 mother 1 3 0 no yes yes yes
## 5 father 1 2 0 no yes yes no
## 6 mother 1 2 0 no yes yes yes
## nursery higher internet romantic famrel freetime goout Dalc Walc health
## 1 yes yes no no 4 3 4 1 1 3
## 2 no yes yes no 5 3 3 1 1 3
## 3 yes yes yes no 4 3 2 2 3 3
## 4 yes yes yes yes 3 2 2 1 1 5
## 5 yes yes no no 4 3 2 1 2 5
## 6 yes yes yes no 5 4 2 1 2 5
## absences G1 G2 G3 Var Var2
## 1 6 5 6 6 All 1
## 2 4 5 5 6 All 2
## 3 10 7 8 10 All 3
## 4 2 15 14 15 All 4
## 5 4 6 10 10 All 5
## 6 10 15 15 15 All 6## school sex age address famsize Pstatus Medu Fedu Mjob Fjob reason
## 1 GP F 18 U GT3 A 4 4 at_home teacher course
## 2 GP F 17 U GT3 T 1 1 at_home other course
## 3 GP F 15 U LE3 T 1 1 at_home other other
## 4 GP F 15 U GT3 T 4 2 health services home
## 5 GP F 16 U GT3 T 3 3 other other home
## 6 GP M 16 U LE3 T 4 3 services other reputation
## guardian traveltime studytime failures schoolsup famsup paid activities
## 1 mother 2 2 0 yes no no no
## 2 father 1 2 0 no yes no no
## 3 mother 1 2 0 yes no no no
## 4 mother 1 3 0 no yes no yes
## 5 father 1 2 0 no yes no no
## 6 mother 1 2 0 no yes no yes
## nursery higher internet romantic famrel freetime goout Dalc Walc health
## 1 yes yes no no 4 3 4 1 1 3
## 2 no yes yes no 5 3 3 1 1 3
## 3 yes yes yes no 4 3 2 2 3 3
## 4 yes yes yes yes 3 2 2 1 1 5
## 5 yes yes no no 4 3 2 1 2 5
## 6 yes yes yes no 5 4 2 1 2 5
## absences G1 G2 G3 Var
## 1 4 0 11 11 All
## 2 2 9 11 11 All
## 3 6 12 13 12 All
## 4 0 14 14 14 All
## 5 0 11 13 13 All
## 6 6 12 12 13 AllThe data frame presents about 30 factors and 03 variables (G1, G2 and G3). These 03 variables are interesting as there are students’s grades.
G1: first period grade (numeric: from 0 to 20)
G2: second period grade (numeric: from 0 to 20)
G3: final grade (numeric: from 0 to 20)Let’s keep in mind the research questions. Do students at “GP” - Gabriel Pereira school or “MS” - Mousinho da Silveira school perform well? If yes, what are the factors contributing to students’s success? If no, what are the factors leading to students’ poor performance? One way to go about these questions is to look at the 03 variables. These 03 variable can summary to one key element-That element is student’s performance.
Let’s take a closer look at these 03 variables. We might throw in a biais by neglecting the fact that there are two schools in the data frame. How significant is each school into the data frame.
## student_math$school
## n missing distinct
## 395 0 2
##
## Value GP MS
## Frequency 349 46
## Proportion 0.884 0.116## [1] "Students dristribution from each school are: 88.4% students for Gabriel Pereira School and 11.6% students for Mousinho da Silveira School"
- Actually, we could check the age distribution in the Math course
## student_math$sex
## n missing distinct
## 395 0 2
##
## Value F M
## Frequency 208 187
## Proportion 0.527 0.473
- Age and sex distribution in the Math course
- First, we need to organize the data frame into two data frame that represents the two schools.
## school sex age address famsize Pstatus Medu Fedu Mjob Fjob reason
## 1 MS M 18 R GT3 T 3 2 other other course
## 2 MS M 19 R GT3 T 1 1 other services home
## 3 MS M 17 U GT3 T 3 3 health other course
## 4 MS M 18 U LE3 T 1 3 at_home services course
## 5 MS M 19 R GT3 T 1 1 other other home
## 6 MS M 17 R GT3 T 4 3 services other home
## guardian traveltime studytime failures schoolsup famsup paid activities
## 1 mother 2 1 1 no yes no no
## 2 other 3 2 3 no no no no
## 3 mother 2 2 0 no yes yes no
## 4 mother 1 1 1 no no no no
## 5 other 3 1 1 no yes no no
## 6 mother 2 2 0 no yes yes yes
## nursery higher internet romantic famrel freetime goout Dalc Walc health
## 1 no yes yes no 2 5 5 5 5 5
## 2 yes yes yes no 5 4 4 3 3 2
## 3 yes yes yes no 4 5 4 2 3 3
## 4 yes no yes yes 4 3 3 2 3 3
## 5 yes yes yes no 4 4 4 3 3 5
## 6 no yes yes yes 4 5 5 1 3 2
## absences G1 G2 G3 Var Var2 grade1 grade2 grade3
## 1 10 11 13 13 All 350 C C C
## 2 8 8 7 8 All 351 D D D
## 3 2 13 13 13 All 352 C C C
## 4 7 8 7 8 All 353 D D D
## 5 4 8 8 8 All 354 D D D
## 6 4 13 11 11 All 355 C C C## Let's do summary on Math result 1 for students from Gabriel Pereira School## student_math_GP$G1
## n missing distinct Info Mean Gmd .05 .10
## 349 0 17 0.992 10.94 3.791 6 7
## .25 .50 .75 .90 .95
## 8 11 13 16 16
##
## lowest : 3 4 5 6 7, highest: 15 16 17 18 19
##
## Value 3 4 5 6 7 8 9 10 11 12 13
## Frequency 1 1 7 19 32 35 30 45 34 32 27
## Proportion 0.003 0.003 0.020 0.054 0.092 0.100 0.086 0.129 0.097 0.092 0.077
##
## Value 14 15 16 17 18 19
## Frequency 27 21 21 8 7 2
## Proportion 0.077 0.060 0.060 0.023 0.020 0.006Let’s see the mean, max for students from Gabriel Pereira School
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.00 8.00 11.00 10.94 13.00 19.00
