t = "E:\\2. NCS hồ sơ- tiến trình học 2024\\8.1. Viết báo quốc tế\\45. Lớp học phân tích dữ liệu. Đại học Văn Lang. T12.2022\\Arrest data.csv"
arr = read.csv (t)
head (arr)## id week arrest finance age race work married parole prior educ
## 1 1 20 1 no 27 black no not married yes 3 3
## 2 2 17 1 no 18 black no not married yes 8 4
## 3 3 25 1 no 19 other yes not married yes 13 3
## 4 4 52 0 yes 23 black yes married yes 1 5
## 5 5 52 0 no 19 other yes not married yes 3 3
## 6 6 52 0 no 24 black yes not married no 2 4dim (arr)## [1] 432 11head (arr)## id week arrest finance age race work married parole prior educ
## 1 1 20 1 no 27 black no not married yes 3 3
## 2 2 17 1 no 18 black no not married yes 8 4
## 3 3 25 1 no 19 other yes not married yes 13 3
## 4 4 52 0 yes 23 black yes married yes 1 5
## 5 5 52 0 no 19 other yes not married yes 3 3
## 6 6 52 0 no 24 black yes not married no 2 4tail (arr)## id week arrest finance age race work married parole prior educ
## 427 427 12 1 yes 22 black yes married yes 2 4
## 428 428 52 0 yes 31 other yes not married yes 3 3
## 429 429 52 0 no 20 black no not married yes 1 4
## 430 430 52 0 yes 20 black yes married yes 1 3
## 431 431 52 0 no 29 black yes not married yes 3 4
## 432 432 52 0 yes 24 black yes not married yes 1 4arr$arrest1[arr$arrest==1] = "Yes"
arr$arrest1 [arr$arrest==0] = "No"
table (arr$arrest1, arr$arrest)##
## 0 1
## No 318 0
## Yes 0 114head (arr)## id week arrest finance age race work married parole prior educ arrest1
## 1 1 20 1 no 27 black no not married yes 3 3 Yes
## 2 2 17 1 no 18 black no not married yes 8 4 Yes
## 3 3 25 1 no 19 other yes not married yes 13 3 Yes
## 4 4 52 0 yes 23 black yes married yes 1 5 No
## 5 5 52 0 no 19 other yes not married yes 3 3 No
## 6 6 52 0 no 24 black yes not married no 2 4 Noarr$fin [arr$finance=="yes"] = 1
arr$fin [arr$finance=="no"] = 0
head (arr)## id week arrest finance age race work married parole prior educ arrest1
## 1 1 20 1 no 27 black no not married yes 3 3 Yes
## 2 2 17 1 no 18 black no not married yes 8 4 Yes
## 3 3 25 1 no 19 other yes not married yes 13 3 Yes
## 4 4 52 0 yes 23 black yes married yes 1 5 No
## 5 5 52 0 no 19 other yes not married yes 3 3 No
## 6 6 52 0 no 24 black yes not married no 2 4 No
## fin
## 1 0
## 2 0
## 3 0
## 4 1
## 5 0
## 6 0summary (arr)## id week arrest finance
## Min. : 1.0 Min. : 1.00 Min. :0.0000 Length:432
## 1st Qu.:108.8 1st Qu.:50.00 1st Qu.:0.0000 Class :character
## Median :216.5 Median :52.00 Median :0.0000 Mode :character
## Mean :216.5 Mean :45.85 Mean :0.2639
## 3rd Qu.:324.2 3rd Qu.:52.00 3rd Qu.:1.0000
## Max. :432.0 Max. :52.00 Max. :1.0000
## age race work married
## Min. :17.0 Length:432 Length:432 Length:432
## 1st Qu.:20.0 Class :character Class :character Class :character
## Median :23.0 Mode :character Mode :character Mode :character
## Mean :24.6
## 3rd Qu.:27.0
## Max. :44.0
## parole prior educ arrest1
## Length:432 Min. : 0.000 Min. :2.000 Length:432
## Class :character 1st Qu.: 1.000 1st Qu.:3.000 Class :character
## Mode :character Median : 2.000 Median :3.000 Mode :character
## Mean : 2.984 Mean :3.477
## 3rd Qu.: 4.000 3rd Qu.:4.000
## Max. :18.000 Max. :6.000
## fin
## Length:432
## Class :character
## Mode :character
##
##
## library(table1)##
## Attaching package: 'table1'## The following objects are masked from 'package:base':
##
## units, units<-table1(~ week+ arrest + arrest1+ age+ work+ married+ parole+ prior+ educ+ fin, data = arr)| Overall (N=432) |
|
|---|---|
| week | |
| Mean (SD) | 45.9 (12.7) |
| Median [Min, Max] | 52.0 [1.00, 52.0] |
| arrest | |
| Mean (SD) | 0.264 (0.441) |
| Median [Min, Max] | 0 [0, 1.00] |
| arrest1 | |
| No | 318 (73.6%) |
| Yes | 114 (26.4%) |
| age | |
| Mean (SD) | 24.6 (6.11) |
| Median [Min, Max] | 23.0 [17.0, 44.0] |
| work | |
| no | 185 (42.8%) |
| yes | 247 (57.2%) |
| married | |
| married | 53 (12.3%) |
| not married | 379 (87.7%) |
| parole | |
| no | 165 (38.2%) |
| yes | 267 (61.8%) |
| prior | |
| Mean (SD) | 2.98 (2.90) |
| Median [Min, Max] | 2.00 [0, 18.0] |
| educ | |
| Mean (SD) | 3.48 (0.834) |
| Median [Min, Max] | 3.00 [2.00, 6.00] |
| fin | |
| 0 | 216 (50.0%) |
| 1 | 216 (50.0%) |
table1(~ week+ arrest + arrest1+ age+ work+ married+ parole+ prior+ educ| finance, data = arr)| no (N=216) |
yes (N=216) |
Overall (N=432) |
|
|---|---|---|---|
| week | |||
| Mean (SD) | 44.8 (13.5) | 46.9 (11.7) | 45.9 (12.7) |
| Median [Min, Max] | 52.0 [1.00, 52.0] | 52.0 [7.00, 52.0] | 52.0 [1.00, 52.0] |
| arrest | |||
| Mean (SD) | 0.306 (0.462) | 0.222 (0.417) | 0.264 (0.441) |
| Median [Min, Max] | 0 [0, 1.00] | 0 [0, 1.00] | 0 [0, 1.00] |
| arrest1 | |||
| No | 150 (69.4%) | 168 (77.8%) | 318 (73.6%) |
| Yes | 66 (30.6%) | 48 (22.2%) | 114 (26.4%) |
| age | |||
| Mean (SD) | 24.2 (5.73) | 25.0 (6.47) | 24.6 (6.11) |
| Median [Min, Max] | 23.0 [17.0, 44.0] | 23.0 [17.0, 44.0] | 23.0 [17.0, 44.0] |
| work | |||
| no | 93 (43.1%) | 92 (42.6%) | 185 (42.8%) |
| yes | 123 (56.9%) | 124 (57.4%) | 247 (57.2%) |
| married | |||
| married | 29 (13.4%) | 24 (11.1%) | 53 (12.3%) |
| not married | 187 (86.6%) | 192 (88.9%) | 379 (87.7%) |
| parole | |||
| no | 81 (37.5%) | 84 (38.9%) | 165 (38.2%) |
| yes | 135 (62.5%) | 132 (61.1%) | 267 (61.8%) |
| prior | |||
| Mean (SD) | 2.99 (2.92) | 2.98 (2.88) | 2.98 (2.90) |
| Median [Min, Max] | 2.00 [0, 18.0] | 2.00 [0, 15.0] | 2.00 [0, 18.0] |
| educ | |||
| Mean (SD) | 3.44 (0.844) | 3.52 (0.824) | 3.48 (0.834) |
| Median [Min, Max] | 3.00 [2.00, 6.00] | 3.00 [2.00, 6.00] | 3.00 [2.00, 6.00] |