-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathcalculatePR_TE_H.Rmd
250 lines (226 loc) · 13 KB
/
calculatePR_TE_H.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
---
title: "Calculate Page rank, Target Entropy, and Hide"
author: "Jesper Bruun & Adrienne Traxleer"
date: "3/28/2020"
output: github_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## Required functions
```{r cars}
#required functions
source("functions/tarEnt.r")
source("functions/searchInf.r")
```
## Calculating Page rank
```{r pagerank, eval=F}
#pagerank
accPS_PR<-lapply(accPS,page.rank)
accCD_PR<-lapply(accCD,page.rank)
accICS_PR<-lapply(accICS,page.rank)
singlePS_PR<-lapply(weeksPS,page.rank)
singleCD_PR<-lapply(weeksCD,page.rank)
singleICS_PR<-lapply(weeksICS,page.rank)
```
## Calculating Target Entropy
```{r targetentropy, eval=F}
#target entropy
accPS_TE<-lapply(accPS,TargetEntropy)
accCD_TE<-lapply(accCD,TargetEntropy)
accICS_TE<-lapply(accICS,TargetEntropy)
singlePS_TE<-lapply(weeksPS,TargetEntropy)
singleCD_TE<-lapply(weeksCD,TargetEntropy)
singleICS_TE<-lapply(weeksICS,TargetEntropy)
```
## Calculating Hide
```{r hide, eval=F}
#hide
accPS_S<-lapply(accPS,sInfMatrix)
accCD_S<-lapply(accCD,sInfMatrix)
accICS_S<-lapply(accICS,sInfMatrix)
singlePS_S<-lapply(weeksPS,sInfMatrix)
singleCD_S<-lapply(weeksCD,sInfMatrix)
singleICS_S<-lapply(weeksICS,sInfMatrix)
accPS_H<-lapply(accPS_S,colSums,na.rm=T)
accCD_H<-lapply(accCD_S,colSums,na.rm=T)
accICS_H<-lapply(accICS_S,colSums,na.rm=T)
singlePS_H<-lapply(singlePS_S,colSums,na.rm=T)
singleCD_H<-lapply(singleCD_S,colSums,na.rm=T)
singleICS_H<-lapply(singleICS_S,colSums,na.rm=T)
```
## .RData file with calculations done
THE PRTEH.RData file contains all calculations
Here, we load the file and make som comparisons.
```{r loadPRTEH, echo=T, eval=T}
load("data/PRTEH.RData")
```
We want to figure out whether there are differences in passing and failing that may be connected to other attributes. We use wilcoxon tests per default, since we do not assume distributions to be normal. There seems to be no gender differences.
```{r testgender, echo=T}
wilcox.test(V(accPS[[1]])$grade[V(accPS[[1]])$gender==1],V(accPS[[1]])$grade[V(accPS[[1]])$gender==0])
wilcox.test(V(accPS[[1]])$pass[V(accPS[[1]])$gender==1],V(accPS[[1]])$pass[V(accPS[[1]])$gender==0])
wilcox.test(V(accPS[[1]])$justpass[V(accPS[[1]])$gender==1],V(accPS[[1]])$justpass[V(accPS[[1]])$gender==0])
```
### FCI NAs excluded
```{r testFCI1, echo=T}
par(mfrow=c(2,2))
plot(table(V(accPS[[1]])$fci_pre[V(accPS[[1]])$pass==1]),ylab="N",xlab="score",main="FCI pre of passing students")
plot(table(V(accPS[[1]])$fci_pre[V(accPS[[1]])$pass==0]),ylab="N",xlab="score",main="FCI pre of failing students")
plot(table(V(accPS[[1]])$fci_pre[V(accPS[[1]])$justpass==1]),ylab="N",xlab="score",main="FCI pre of just passing students")
plot(table(V(accPS[[1]])$fci_pre[V(accPS[[1]])$justpass==0]),ylab="N",xlab="score",main="FCI pre of just failing students")
```
### FCI impute 0 if NA
```{r testFCI2, echo=T}
par(mfrow=c(2,2))
plot(table(V(accPS[[1]])$fci_pre_0[V(accPS[[1]])$pass==1]),ylab="N",xlab="score",main="FCI pre of passing students")
plot(table(V(accPS[[1]])$fci_pre_0[V(accPS[[1]])$pass==0]),ylab="N",xlab="score",main="FCI pre of failing students")
plot(table(V(accPS[[1]])$fci_pre_0[V(accPS[[1]])$justpass==1]),ylab="N",xlab="score",main="FCI pre of just passing students")
plot(table(V(accPS[[1]])$fci_pre_0[V(accPS[[1]])$justpass==0]),ylab="N",xlab="score",main="FCI pre of just failing students")
```
### FCI impute random score selected from others with same grade if NA
```{r testFCI3, echo=T}
par(mfrow=c(2,2))
plot(table(V(accPS[[1]])$fci_pre_s[V(accPS[[1]])$pass==1]),ylab="N",xlab="score",main="FCI pre of passing students")
plot(table(V(accPS[[1]])$fci_pre_s[V(accPS[[1]])$pass==0]),ylab="N",xlab="score",main="FCI pre of failing students")
plot(table(V(accPS[[1]])$fci_pre_s[V(accPS[[1]])$justpass==1]),ylab="N",xlab="score",main="FCI pre of just passing students")
plot(table(V(accPS[[1]])$fci_pre_s[V(accPS[[1]])$justpass==0]),ylab="N",xlab="score",main="FCI pre of just failing students")
```
### FCI categories
```{r testFCI4, echo=T}
par(mfrow=c(2,2))
plot(table(V(accPS[[1]])$fci_pre_c[V(accPS[[1]])$pass==1]),ylab="N",xlab="score",main="FCI pre of passing students")
plot(table(V(accPS[[1]])$fci_pre_c[V(accPS[[1]])$pass==0]),ylab="N",xlab="score",main="FCI pre of failing students")
plot(table(V(accPS[[1]])$fci_pre_c[V(accPS[[1]])$justpass==1]),ylab="N",xlab="score",main="FCI pre of just passing students")
plot(table(V(accPS[[1]])$fci_pre_c[V(accPS[[1]])$justpass==0]),ylab="N",xlab="score",main="FCI pre of just failing students")
```
### Section number
```{r testcohort, echo=T}
par(mfrow=c(1,2))
c1<-table(V(accPS[[1]])$pass[V(accPS[[1]])$cohort==1])/length(which(V(accPS[[1]])$cohort==1))
c2<-table(V(accPS[[1]])$pass[V(accPS[[1]])$cohort==2])/length(which(V(accPS[[1]])$cohort==2))
c3<-table(V(accPS[[1]])$pass[V(accPS[[1]])$cohort==3])/length(which(V(accPS[[1]])$cohort==3))
c4<-table(V(accPS[[1]])$pass[V(accPS[[1]])$cohort==4])/length(which(V(accPS[[1]])$cohort==4))
c5<-table(V(accPS[[1]])$pass[V(accPS[[1]])$cohort==5])/length(which(V(accPS[[1]])$cohort==5))
c6<-table(V(accPS[[1]])$pass[V(accPS[[1]])$cohort==6])/length(which(V(accPS[[1]])$cohort==6))
c10<-table(V(accPS[[1]])$pass[V(accPS[[1]])$cohort==10])/length(which(V(accPS[[1]])$cohort==10))
cohfail<-c(c1[1],c2[1],c3[1],c4[1],c5[1],c6[1],c10[1])
cohpass<-c(c1[2],c2[2],c3[2],c4[2],c5[2],c6[2],c10[2])
plot(cohpass,xlab="Section number",ylab="Fraction",ylim=c(0,1),main="Passing and failing per section",col="darkgreen")
points(cohfail,col="red")
cj1<-table(V(accPS[[1]])$justpass[V(accPS[[1]])$cohort==1])/length(which(V(accPS[[1]])$cohort==1))
cj2<-table(V(accPS[[1]])$justpass[V(accPS[[1]])$cohort==2])/length(which(V(accPS[[1]])$cohort==2))
cj3<-table(V(accPS[[1]])$justpass[V(accPS[[1]])$cohort==3])/length(which(V(accPS[[1]])$cohort==3))
cj4<-table(V(accPS[[1]])$justpass[V(accPS[[1]])$cohort==4])/length(which(V(accPS[[1]])$cohort==4))
cj5<-table(V(accPS[[1]])$justpass[V(accPS[[1]])$cohort==5])/length(which(V(accPS[[1]])$cohort==5))
cj6<-table(V(accPS[[1]])$justpass[V(accPS[[1]])$cohort==6])/length(which(V(accPS[[1]])$cohort==6))
cj10<-table(V(accPS[[1]])$justpass[V(accPS[[1]])$cohort==10])/length(which(V(accPS[[1]])$cohort==10))
cohjfail<-c(cj1[1],cj2[1],cj3[1],cj4[1],cj5[1],cj6[1],cj10[1])
cohjpass<-c(cj1[2],cj2[2],cj3[2],cj4[2],cj5[2],cj6[2],cj10[2])
plot(cohjpass,xlab="Section number",ylab="Fraction of whole section",ylim=c(0,1),main="Just passing vs just failing",col="darkgreen")
points(cohjfail,col="red")
```
## Problem solving layer
### Page rank difference
```{r testpagerank, echo=T}
par(mfrow=c(2,2))
hist(accPS_PR[[7]]$vector[V(accPS[[7]])$pass==1],main="Pagerank of passing")
hist(accPS_PR[[7]]$vector[V(accPS[[7]])$pass==0],main="Pagerank of failing")
hist(accPS_PR[[7]]$vector[V(accPS[[7]])$justpass==1],main="Pagerank of just passing")
hist(accPS_PR[[7]]$vector[V(accPS[[7]])$justpass==0],main="Pagerank of just failing")
t.test(accPS_PR[[7]]$vector[V(accPS[[7]])$pass==1],accPS_PR[[7]]$vector[V(accPS[[7]])$pass==0])
wilcox.test(accPS_PR[[7]]$vector[V(accPS[[7]])$pass==1],accPS_PR[[7]]$vector[V(accPS[[7]])$pass==0])
t.test(accPS_PR[[7]]$vector[V(accPS[[7]])$justpass==1],accPS_PR[[7]]$vector[V(accPS[[7]])$justpass==0])
wilcox.test(accPS_PR[[7]]$vector[V(accPS[[7]])$justpass==1],accPS_PR[[7]]$vector[V(accPS[[7]])$justpass==0])
```
```{r testtargetentropy, echo=T}
par(mfrow=c(2,2))
hist(accPS_TE[[7]][V(accPS[[7]])$pass==1],main="Target Entropy of passing")
hist(accPS_TE[[7]][V(accPS[[7]])$pass==0],main="Target Entropy of failing")
hist(accPS_TE[[7]][V(accPS[[7]])$justpass==1],main="Target Entropy of just passing")
hist(accPS_TE[[7]][V(accPS[[7]])$justpass==0],main="Target Entropy of just failing")
t.test(accPS_TE[[7]][V(accPS[[7]])$pass==1],accPS_TE[[7]][V(accPS[[7]])$pass==0])
wilcox.test(accPS_TE[[7]][V(accPS[[7]])$pass==1],accPS_TE[[7]][V(accPS[[7]])$pass==0])
t.test(accPS_TE[[7]][V(accPS[[7]])$justpass==1],accPS_TE[[7]][V(accPS[[7]])$justpass==0])
wilcox.test(accPS_TE[[7]][V(accPS[[7]])$justpass==1],accPS_TE[[7]][V(accPS[[7]])$justpass==0])
```
```{r testhidePS, echo=T}
par(mfrow=c(2,2))
hist(accPS_H[[7]][V(accPS[[7]])$pass==1],main="Hide of passing")
hist(accPS_H[[7]][V(accPS[[7]])$pass==0],main="Hide of failing")
hist(accPS_H[[7]][V(accPS[[7]])$justpass==1],main="Hide of just passing")
hist(accPS_H[[7]][V(accPS[[7]])$justpass==0],main="Hide of just failing")
t.test(accPS_H[[7]][V(accPS[[7]])$pass==1],accPS_H[[7]][V(accPS[[7]])$pass==0])
wilcox.test(accPS_H[[7]][V(accPS[[7]])$pass==1],accPS_H[[7]][V(accPS[[7]])$pass==0])
t.test(accPS_H[[7]][V(accPS[[7]])$justpass==1],accPS_H[[7]][V(accPS[[7]])$justpass==0])
wilcox.test(accPS_H[[7]][V(accPS[[7]])$justpass==1],accPS_H[[7]][V(accPS[[7]])$justpass==0])
```
## Concept Discussion layer
### Page rank difference
```{r testpagerankCD, echo=T}
par(mfrow=c(2,2))
hist(accCD_PR[[7]]$vector[V(accCD[[7]])$pass==1],main="Pagerank of passing")
hist(accCD_PR[[7]]$vector[V(accCD[[7]])$pass==0],main="Pagerank of failing")
hist(accCD_PR[[7]]$vector[V(accCD[[7]])$justpass==1],main="Pagerank of just passing")
hist(accCD_PR[[7]]$vector[V(accCD[[7]])$justpass==0],main="Pagerank of just failing")
t.test(accCD_PR[[7]]$vector[V(accCD[[7]])$pass==1],accCD_PR[[7]]$vector[V(accCD[[7]])$pass==0])
wilcox.test(accCD_PR[[7]]$vector[V(accCD[[7]])$pass==1],accCD_PR[[7]]$vector[V(accCD[[7]])$pass==0])
t.test(accCD_PR[[7]]$vector[V(accCD[[7]])$justpass==1],accCD_PR[[7]]$vector[V(accCD[[7]])$justpass==0])
wilcox.test(accCD_PR[[7]]$vector[V(accCD[[7]])$justpass==1],accCD_PR[[7]]$vector[V(accCD[[7]])$justpass==0])
```
```{r testtargetentropyCD, echo=T}
par(mfrow=c(2,2))
hist(accCD_TE[[7]][V(accCD[[7]])$pass==1],main="Target Entropy of passing")
hist(accCD_TE[[7]][V(accCD[[7]])$pass==0],main="Target Entropy of failing")
hist(accCD_TE[[7]][V(accCD[[7]])$justpass==1],main="Target Entropy of just passing")
hist(accCD_TE[[7]][V(accCD[[7]])$justpass==0],main="Target Entropy of just failing")
t.test(accCD_TE[[7]][V(accCD[[7]])$pass==1],accCD_TE[[7]][V(accCD[[7]])$pass==0])
wilcox.test(accCD_TE[[7]][V(accCD[[7]])$pass==1],accCD_TE[[7]][V(accCD[[7]])$pass==0])
t.test(accCD_TE[[7]][V(accCD[[7]])$justpass==1],accCD_TE[[7]][V(accCD[[7]])$justpass==0])
wilcox.test(accCD_TE[[7]][V(accCD[[7]])$justpass==1],accCD_TE[[7]][V(accCD[[7]])$justpass==0])
```
```{r testhideCD, echo=T}
par(mfrow=c(2,2))
hist(accCD_H[[7]][V(accCD[[7]])$pass==1],main="Hide of passing")
hist(accCD_H[[7]][V(accCD[[7]])$pass==0],main="Hide of failing")
hist(accCD_H[[7]][V(accCD[[7]])$justpass==1],main="Hide of just passing")
hist(accCD_H[[7]][V(accCD[[7]])$justpass==0],main="Hide of just failing")
t.test(accCD_H[[7]][V(accCD[[7]])$pass==1],accCD_H[[7]][V(accCD[[7]])$pass==0])
wilcox.test(accCD_H[[7]][V(accCD[[7]])$pass==1],accCD_H[[7]][V(accCD[[7]])$pass==0])
t.test(accCD_H[[7]][V(accCD[[7]])$justpass==1],accCD_H[[7]][V(accCD[[7]])$justpass==0])
wilcox.test(accCD_H[[7]][V(accCD[[7]])$justpass==1],accCD_H[[7]][V(accCD[[7]])$justpass==0])
```
## In Class Social layer
### Page rank difference
```{r testpagerankICS, echo=T}
par(mfrow=c(2,2))
hist(accICS_PR[[7]]$vector[V(accICS[[7]])$pass==1],main="Pagerank of passing")
hist(accICS_PR[[7]]$vector[V(accICS[[7]])$pass==0],main="Pagerank of failing")
hist(accICS_PR[[7]]$vector[V(accICS[[7]])$justpass==1],main="Pagerank of just passing")
hist(accICS_PR[[7]]$vector[V(accICS[[7]])$justpass==0],main="Pagerank of just failing")
t.test(accICS_PR[[7]]$vector[V(accICS[[7]])$pass==1],accICS_PR[[7]]$vector[V(accICS[[7]])$pass==0])
wilcox.test(accICS_PR[[7]]$vector[V(accICS[[7]])$pass==1],accICS_PR[[7]]$vector[V(accICS[[7]])$pass==0])
t.test(accICS_PR[[7]]$vector[V(accICS[[7]])$justpass==1],accICS_PR[[7]]$vector[V(accICS[[7]])$justpass==0])
wilcox.test(accICS_PR[[7]]$vector[V(accICS[[7]])$justpass==1],accICS_PR[[7]]$vector[V(accICS[[7]])$justpass==0])
```
```{r testtargetentropyICS, echo=T}
par(mfrow=c(2,2))
hist(accICS_TE[[7]][V(accICS[[7]])$pass==1],main="Target Entropy of passing")
hist(accICS_TE[[7]][V(accICS[[7]])$pass==0],main="Target Entropy of failing")
hist(accICS_TE[[7]][V(accICS[[7]])$justpass==1],main="Target Entropy of just passing")
hist(accICS_TE[[7]][V(accICS[[7]])$justpass==0],main="Target Entropy of just failing")
t.test(accICS_TE[[7]][V(accICS[[7]])$pass==1],accICS_TE[[7]][V(accICS[[7]])$pass==0])
wilcox.test(accICS_TE[[7]][V(accICS[[7]])$pass==1],accICS_TE[[7]][V(accICS[[7]])$pass==0])
t.test(accICS_TE[[7]][V(accICS[[7]])$justpass==1],accICS_TE[[7]][V(accICS[[7]])$justpass==0])
wilcox.test(accICS_TE[[7]][V(accICS[[7]])$justpass==1],accICS_TE[[7]][V(accICS[[7]])$justpass==0])
```
```{r testhideICS, echo=T}
par(mfrow=c(2,2))
hist(accICS_H[[7]][V(accICS[[7]])$pass==1],main="Hide of passing")
hist(accICS_H[[7]][V(accICS[[7]])$pass==0],main="Hide of failing")
hist(accICS_H[[7]][V(accICS[[7]])$justpass==1],main="Hide of just passing")
hist(accICS_H[[7]][V(accICS[[7]])$justpass==0],main="Hide of just failing")
t.test(accICS_H[[7]][V(accICS[[7]])$pass==1],accICS_H[[7]][V(accICS[[7]])$pass==0])
wilcox.test(accICS_H[[7]][V(accICS[[7]])$pass==1],accICS_H[[7]][V(accICS[[7]])$pass==0])
t.test(accICS_H[[7]][V(accICS[[7]])$justpass==1],accICS_H[[7]][V(accICS[[7]])$justpass==0])
wilcox.test(accICS_H[[7]][V(accICS[[7]])$justpass==1],accICS_H[[7]][V(accICS[[7]])$justpass==0])
```