#NHAP LIEU
datalikert=read.csv("/Users/lelyy/Desktop/Likert.csv",header=TRUE)
save(datalikert,file = "datalikert.rda")
attach(datalikert)
is.data.frame(datalikert)
## [1] TRUE
head(datalikert)
## STT GTINH TDO DTUOI TNHAP A1 A2 A3 A4 A5 B1 B2 B3 B4 C1 C2 C3 C4 D1 D2 D3 E1
## 1 1 2 4 1 3 5 5 3 5 4 3 2 3 4 5 5 4 4 4 5 4 2
## 2 2 2 2 2 3 3 3 3 5 4 4 5 4 5 2 3 3 2 3 4 3 3
## 3 3 2 4 1 2 3 3 3 3 3 4 4 4 5 4 4 3 4 3 4 4 4
## 4 4 1 4 2 2 5 3 3 4 4 5 5 5 5 1 2 4 3 5 4 1 3
## 5 5 2 3 1 1 5 3 3 5 4 3 3 3 3 3 4 3 3 4 4 3 4
## 6 6 1 4 2 2 5 3 3 5 4 3 4 3 3 3 4 5 3 2 3 3 4
## E2 E3 E4 F1 F2 F3 F4 F5 Atb Btb Ctb Dtb Etb Ftb
## 1 3 3 4 4 5 3 4 5 4.4 3.00 4.50 4.33 3.00 4.2
## 2 4 3 4 3 3 3 4 5 3.6 4.50 2.50 3.33 3.50 3.6
## 3 3 3 4 4 4 4 4 5 3.0 4.25 3.75 3.67 3.50 4.2
## 4 4 3 4 5 5 4 4 5 3.8 5.00 2.50 3.33 3.50 4.6
## 5 3 3 4 2 5 4 4 5 4.0 3.00 3.25 3.67 3.50 4.0
## 6 4 3 4 3 3 5 4 5 4.0 3.25 3.75 2.67 3.75 4.0
dim(datalikert)
## [1] 198 36
#cau 1
#thong ke cac bien
library(psych)
ABCDEFtb=data.frame(Atb,Btb,Ctb,Dtb,Etb,Ftb)
describe(ABCDEFtb)
## vars n mean sd median trimmed mad min max range skew kurtosis se
## Atb 1 198 4.06 0.72 4.00 4.08 1.19 2.20 5 2.80 -0.15 -1.14 0.05
## Btb 2 198 3.95 0.83 4.00 4.04 1.11 1.25 5 3.75 -0.89 0.37 0.06
## Ctb 3 198 3.68 0.87 3.62 3.71 0.93 1.50 5 3.50 -0.11 -0.61 0.06
## Dtb 4 198 3.80 0.78 4.00 3.85 0.49 1.00 5 4.00 -0.68 0.71 0.06
## Etb 5 198 3.95 0.81 4.00 4.04 0.74 1.25 5 3.75 -0.97 1.02 0.06
## Ftb 6 198 3.85 0.74 3.90 3.84 1.04 2.00 5 3.00 -0.04 -1.12 0.05
#tinh mode bien A1
#install.packages(c("DescTools","readxl"))
#library(readxl)
library(DescTools)
##
## Attaching package: 'DescTools'
## The following objects are masked from 'package:psych':
##
## AUC, ICC, SD
#install.packages("readxl", type = "source")
#install.packages("DescTools", type = "source")
Mode(A1)
## [1] 5
## attr(,"freq")
## [1] 94
table(A1)
## A1
## 3 4 5
## 65 39 94
#Nhan xet cau 1: bien co gia tri trung #binh cao #nhat la Atb = 4.06
#Bien co do phan tan lon nhat la bien Ctb = 0.87
#Mode cua bien A1 la 5 voi 94 quan sat
#cau 2
#ma hoa bien gioi tinh
GTINHMH=GTINH
GTINHMH=replace(GTINHMH,GTINH==1,"Nam")
GTINHMH=replace(GTINHMH,GTINH==2,"NU")
GTcode=data.frame(GTINH,GTINHMH)
GTcode
## GTINH GTINHMH
## 1 2 NU
## 2 2 NU
## 3 2 NU
## 4 1 Nam
## 5 2 NU
## 6 1 Nam
## 7 1 Nam
## 8 1 Nam
## 9 2 NU
## 10 1 Nam
## 11 1 Nam
## 12 1 Nam
## 13 2 NU
## 14 1 Nam
## 15 2 NU
## 16 1 Nam
## 17 1 Nam
## 18 1 Nam
## 19 2 NU
## 20 1 Nam
## 21 1 Nam
## 22 1 Nam
## 23 1 Nam
## 24 1 Nam
## 25 1 Nam
## 26 1 Nam
## 27 1 Nam
## 28 1 Nam
## 29 1 Nam
## 30 2 NU
## 31 2 NU
## 32 2 NU
## 33 1 Nam
## 34 2 NU
## 35 2 NU
## 36 2 NU
## 37 1 Nam
## 38 2 NU
## 39 1 Nam
## 40 1 Nam
## 41 1 Nam
## 42 2 NU
## 43 1 Nam
## 44 2 NU
## 45 1 Nam
## 46 1 Nam
## 47 2 NU
## 48 1 Nam
## 49 2 NU
## 50 2 NU
## 51 1 Nam
## 52 2 NU
## 53 2 NU
## 54 1 Nam
## 55 2 NU
## 56 2 NU
## 57 1 Nam
## 58 2 NU
## 59 2 NU
## 60 2 NU
## 61 2 NU
## 62 2 NU
## 63 2 NU
## 64 2 NU
## 65 2 NU
## 66 1 Nam
## 67 1 Nam
## 68 2 NU
## 69 2 NU
## 70 2 NU
## 71 2 NU
## 72 2 NU
## 73 2 NU
## 74 1 Nam
## 75 2 NU
## 76 2 NU
## 77 2 NU
## 78 2 NU
## 79 1 Nam
## 80 2 NU
## 81 2 NU
## 82 2 NU
## 83 1 Nam
## 84 2 NU
## 85 1 Nam
## 86 1 Nam
## 87 1 Nam
## 88 2 NU
## 89 1 Nam
## 90 2 NU
## 91 1 Nam
## 92 1 Nam
## 93 2 NU
## 94 1 Nam
## 95 2 NU
## 96 2 NU
## 97 1 Nam
## 98 2 NU
## 99 2 NU
## 100 1 Nam
## 101 2 NU
## 102 2 NU
## 103 1 Nam
## 104 1 Nam
## 105 1 Nam
## 106 1 Nam
## 107 1 Nam
## 108 1 Nam
## 109 2 NU
## 110 1 Nam
## 111 2 NU
## 112 1 Nam
## 113 2 NU
## 114 2 NU
## 115 1 Nam
## 116 2 NU
## 117 1 Nam
## 118 1 Nam
## 119 1 Nam
## 120 1 Nam
## 121 1 Nam
## 122 1 Nam
## 123 1 Nam
## 124 1 Nam
## 125 1 Nam
## 126 1 Nam
## 127 1 Nam
## 128 1 Nam
## 129 1 Nam
## 130 1 Nam
## 131 2 NU
## 132 2 NU
## 133 1 Nam
## 134 1 Nam
## 135 2 NU
## 136 2 NU
## 137 1 Nam
## 138 2 NU
## 139 1 Nam
## 140 1 Nam
## 141 2 NU
## 142 1 Nam
## 143 2 NU
## 144 1 Nam
## 145 1 Nam
## 146 1 Nam
## 147 1 Nam
## 148 1 Nam
## 149 1 Nam
## 150 1 Nam
## 151 1 Nam
## 152 1 Nam
## 153 1 Nam
## 154 1 Nam
## 155 1 Nam
## 156 1 Nam
## 157 1 Nam
## 158 1 Nam
## 159 1 Nam
## 160 1 Nam
## 161 1 Nam
## 162 1 Nam
## 163 1 Nam
## 164 2 NU
## 165 2 NU
## 166 1 Nam
## 167 2 NU
## 168 1 Nam
## 169 1 Nam
## 170 1 Nam
## 171 1 Nam
## 172 2 NU
## 173 1 Nam
## 174 2 NU
## 175 1 Nam
## 176 2 NU
## 177 1 Nam
## 178 1 Nam
## 179 1 Nam
## 180 2 NU
## 181 1 Nam
## 182 1 Nam
## 183 2 NU
## 184 2 NU
## 185 1 Nam
## 186 1 Nam
## 187 1 Nam
## 188 2 NU
## 189 1 Nam
## 190 1 Nam
## 191 1 Nam
## 192 1 Nam
## 193 1 Nam
## 194 1 Nam
## 195 1 Nam
## 196 1 Nam
## 197 1 Nam
## 198 1 Nam
# bang tan so gioi tinh
table(GTINHMH)
## GTINHMH
## Nam NU
## 121 77
table(GTINHMH)/sum(table(GTINHMH))
## GTINHMH
## Nam NU
## 0.6111111 0.3888889
### Nhan xet cau 2: trong tong the 198 nguoi;co 121 nam (61,1%) va 77 nu (38,9%)
#cau 3
# ma hoa bien do tuoi
DTUOIMH=DTUOI
DTUOIMH=replace(DTUOIMH,DTUOI==1,"<20 TUOI")
DTUOIMH=replace(DTUOIMH,DTUOI==2,"TU 20-30 TUOI")
DTUOIMH=replace(DTUOIMH,DTUOI==3,"TU 31-50 TUOI")
DTUOIMH=replace(DTUOIMH,DTUOI==4,"TREN 50 TUOI")
DTcode=data.frame(DTUOI,DTUOIMH)
DTcode
## DTUOI DTUOIMH
## 1 1 <20 TUOI
## 2 2 TU 20-30 TUOI
## 3 1 <20 TUOI
## 4 2 TU 20-30 TUOI
## 5 1 <20 TUOI
## 6 2 TU 20-30 TUOI
## 7 1 <20 TUOI
## 8 1 <20 TUOI
## 9 2 TU 20-30 TUOI
## 10 1 <20 TUOI
## 11 2 TU 20-30 TUOI
## 12 1 <20 TUOI
## 13 2 TU 20-30 TUOI
## 14 1 <20 TUOI
## 15 4 TREN 50 TUOI
## 16 3 TU 31-50 TUOI
## 17 2 TU 20-30 TUOI
## 18 1 <20 TUOI
## 19 3 TU 31-50 TUOI
## 20 4 TREN 50 TUOI
## 21 2 TU 20-30 TUOI
## 22 3 TU 31-50 TUOI
## 23 3 TU 31-50 TUOI
## 24 4 TREN 50 TUOI
## 25 3 TU 31-50 TUOI
## 26 2 TU 20-30 TUOI
## 27 3 TU 31-50 TUOI
## 28 1 <20 TUOI
## 29 3 TU 31-50 TUOI
## 30 3 TU 31-50 TUOI
## 31 2 TU 20-30 TUOI
## 32 3 TU 31-50 TUOI
## 33 3 TU 31-50 TUOI
## 34 4 TREN 50 TUOI
## 35 3 TU 31-50 TUOI
## 36 2 TU 20-30 TUOI
## 37 3 TU 31-50 TUOI
## 38 1 <20 TUOI
## 39 3 TU 31-50 TUOI
## 40 3 TU 31-50 TUOI
## 41 2 TU 20-30 TUOI
## 42 1 <20 TUOI
## 43 3 TU 31-50 TUOI
## 44 1 <20 TUOI
## 45 4 TREN 50 TUOI
## 46 2 TU 20-30 TUOI
## 47 3 TU 31-50 TUOI
## 48 1 <20 TUOI
## 49 3 TU 31-50 TUOI
## 50 4 TREN 50 TUOI
## 51 1 <20 TUOI
## 52 2 TU 20-30 TUOI
## 53 1 <20 TUOI
## 54 3 TU 31-50 TUOI
## 55 4 TREN 50 TUOI
## 56 4 TREN 50 TUOI
## 57 4 TREN 50 TUOI
## 58 3 TU 31-50 TUOI
## 59 3 TU 31-50 TUOI
## 60 4 TREN 50 TUOI
## 61 2 TU 20-30 TUOI
## 62 4 TREN 50 TUOI
## 63 3 TU 31-50 TUOI
## 64 3 TU 31-50 TUOI
## 65 3 TU 31-50 TUOI
## 66 3 TU 31-50 TUOI
## 67 3 TU 31-50 TUOI
## 68 4 TREN 50 TUOI
## 69 3 TU 31-50 TUOI
## 70 4 TREN 50 TUOI
## 71 2 TU 20-30 TUOI
## 72 3 TU 31-50 TUOI
## 73 3 TU 31-50 TUOI
## 74 4 TREN 50 TUOI
## 75 3 TU 31-50 TUOI
## 76 2 TU 20-30 TUOI
## 77 4 TREN 50 TUOI
## 78 4 TREN 50 TUOI
## 79 4 TREN 50 TUOI
## 80 3 TU 31-50 TUOI
## 81 1 <20 TUOI
## 82 2 TU 20-30 TUOI
## 83 3 TU 31-50 TUOI
## 84 3 TU 31-50 TUOI
## 85 2 TU 20-30 TUOI
## 86 3 TU 31-50 TUOI
## 87 2 TU 20-30 TUOI
## 88 1 <20 TUOI
## 89 1 <20 TUOI
## 90 3 TU 31-50 TUOI
## 91 3 TU 31-50 TUOI
## 92 1 <20 TUOI
## 93 2 TU 20-30 TUOI
## 94 3 TU 31-50 TUOI
## 95 1 <20 TUOI
## 96 3 TU 31-50 TUOI
## 97 2 TU 20-30 TUOI
## 98 4 TREN 50 TUOI
## 99 4 TREN 50 TUOI
## 100 2 TU 20-30 TUOI
## 101 2 TU 20-30 TUOI
## 102 2 TU 20-30 TUOI
## 103 1 <20 TUOI
## 104 2 TU 20-30 TUOI
## 105 2 TU 20-30 TUOI
## 106 1 <20 TUOI
## 107 2 TU 20-30 TUOI
## 108 2 TU 20-30 TUOI
## 109 2 TU 20-30 TUOI
## 110 4 TREN 50 TUOI
## 111 3 TU 31-50 TUOI
## 112 2 TU 20-30 TUOI
## 113 3 TU 31-50 TUOI
## 114 3 TU 31-50 TUOI
## 115 4 TREN 50 TUOI
## 116 3 TU 31-50 TUOI
## 117 2 TU 20-30 TUOI
## 118 3 TU 31-50 TUOI
## 119 4 TREN 50 TUOI
## 120 3 TU 31-50 TUOI
## 121 4 TREN 50 TUOI
## 122 3 TU 31-50 TUOI
## 123 2 TU 20-30 TUOI
## 124 3 TU 31-50 TUOI
## 125 4 TREN 50 TUOI
## 126 2 TU 20-30 TUOI
## 127 4 TREN 50 TUOI
## 128 3 TU 31-50 TUOI
## 129 2 TU 20-30 TUOI
## 130 4 TREN 50 TUOI
## 131 3 TU 31-50 TUOI
## 132 3 TU 31-50 TUOI
## 133 2 TU 20-30 TUOI
## 134 3 TU 31-50 TUOI
## 135 3 TU 31-50 TUOI
## 136 4 TREN 50 TUOI
## 137 2 TU 20-30 TUOI
## 138 3 TU 31-50 TUOI
## 139 3 TU 31-50 TUOI
## 140 4 TREN 50 TUOI
## 141 3 TU 31-50 TUOI
## 142 4 TREN 50 TUOI
## 143 3 TU 31-50 TUOI
## 144 2 TU 20-30 TUOI
## 145 3 TU 31-50 TUOI
## 146 3 TU 31-50 TUOI
## 147 3 TU 31-50 TUOI
## 148 4 TREN 50 TUOI
## 149 4 TREN 50 TUOI
## 150 3 TU 31-50 TUOI
## 151 2 TU 20-30 TUOI
## 152 1 <20 TUOI
## 153 3 TU 31-50 TUOI
## 154 1 <20 TUOI
## 155 3 TU 31-50 TUOI
## 156 1 <20 TUOI
## 157 2 TU 20-30 TUOI
## 158 3 TU 31-50 TUOI
## 159 1 <20 TUOI
## 160 2 TU 20-30 TUOI
## 161 3 TU 31-50 TUOI
## 162 3 TU 31-50 TUOI
## 163 1 <20 TUOI
## 164 3 TU 31-50 TUOI
## 165 2 TU 20-30 TUOI
## 166 2 TU 20-30 TUOI
## 167 3 TU 31-50 TUOI
## 168 3 TU 31-50 TUOI
## 169 2 TU 20-30 TUOI
## 170 4 TREN 50 TUOI
## 171 2 TU 20-30 TUOI
## 172 4 TREN 50 TUOI
## 173 4 TREN 50 TUOI
## 174 1 <20 TUOI
## 175 1 <20 TUOI
## 176 3 TU 31-50 TUOI
## 177 3 TU 31-50 TUOI
## 178 1 <20 TUOI
## 179 3 TU 31-50 TUOI
## 180 2 TU 20-30 TUOI
## 181 2 TU 20-30 TUOI
## 182 2 TU 20-30 TUOI
## 183 4 TREN 50 TUOI
## 184 4 TREN 50 TUOI
## 185 3 TU 31-50 TUOI
## 186 1 <20 TUOI
## 187 3 TU 31-50 TUOI
## 188 1 <20 TUOI
## 189 2 TU 20-30 TUOI
## 190 3 TU 31-50 TUOI
## 191 1 <20 TUOI
## 192 1 <20 TUOI
## 193 2 TU 20-30 TUOI
## 194 1 <20 TUOI
## 195 3 TU 31-50 TUOI
## 196 2 TU 20-30 TUOI
## 197 4 TREN 50 TUOI
## 198 4 TREN 50 TUOI
# ma hoa bien thu nhap
TNHAPMH=TNHAP
TNHAPMH=replace(TNHAPMH,TNHAP==1,"<10 TRIEU")
TNHAPMH=replace(TNHAPMH,TNHAP==2,"TU 10-20 TRIEU")
TNHAPMH=replace(TNHAPMH,TNHAP==3,"TREN 20 TRIEU")
TNcode=data.frame(DTUOI,TNHAPMH)
TNcode
## DTUOI TNHAPMH
## 1 1 TREN 20 TRIEU
## 2 2 TREN 20 TRIEU
## 3 1 TU 10-20 TRIEU
## 4 2 TU 10-20 TRIEU
## 5 1 <10 TRIEU
## 6 2 TU 10-20 TRIEU
## 7 1 TREN 20 TRIEU
## 8 1 TU 10-20 TRIEU
## 9 2 TREN 20 TRIEU
## 10 1 TREN 20 TRIEU
## 11 2 TU 10-20 TRIEU
## 12 1 TU 10-20 TRIEU
## 13 2 TU 10-20 TRIEU
## 14 1 TU 10-20 TRIEU
## 15 4 TREN 20 TRIEU
## 16 3 <10 TRIEU
## 17 2 TREN 20 TRIEU
## 18 1 <10 TRIEU
## 19 3 TREN 20 TRIEU
## 20 4 TREN 20 TRIEU
## 21 2 TREN 20 TRIEU
## 22 3 TREN 20 TRIEU
## 23 3 TU 10-20 TRIEU
## 24 4 TU 10-20 TRIEU
## 25 3 <10 TRIEU
## 26 2 TU 10-20 TRIEU
## 27 3 TREN 20 TRIEU
## 28 1 TU 10-20 TRIEU
## 29 3 TREN 20 TRIEU
## 30 3 TREN 20 TRIEU
## 31 2 TU 10-20 TRIEU
## 32 3 TU 10-20 TRIEU
## 33 3 TU 10-20 TRIEU
## 34 4 <10 TRIEU
## 35 3 TU 10-20 TRIEU
## 36 2 TREN 20 TRIEU
## 37 3 TREN 20 TRIEU
## 38 1 TU 10-20 TRIEU
## 39 3 TREN 20 TRIEU
## 40 3 TU 10-20 TRIEU
## 41 2 TU 10-20 TRIEU
## 42 1 TU 10-20 TRIEU
## 43 3 TREN 20 TRIEU
## 44 1 TREN 20 TRIEU
## 45 4 TREN 20 TRIEU
## 46 2 TREN 20 TRIEU
## 47 3 TREN 20 TRIEU
## 48 1 TU 10-20 TRIEU
## 49 3 TU 10-20 TRIEU
## 50 4 TU 10-20 TRIEU
## 51 1 TREN 20 TRIEU
## 52 2 TREN 20 TRIEU
## 53 1 TU 10-20 TRIEU
## 54 3 TU 10-20 TRIEU
## 55 4 TREN 20 TRIEU
## 56 4 TU 10-20 TRIEU
## 57 4 TREN 20 TRIEU
## 58 3 TREN 20 TRIEU
## 59 3 TU 10-20 TRIEU
## 60 4 TU 10-20 TRIEU
## 61 2 TREN 20 TRIEU
## 62 4 TREN 20 TRIEU
## 63 3 TU 10-20 TRIEU
## 64 3 <10 TRIEU
## 65 3 TREN 20 TRIEU
## 66 3 TU 10-20 TRIEU
## 67 3 TU 10-20 TRIEU
## 68 4 TU 10-20 TRIEU
## 69 3 TREN 20 TRIEU
## 70 4 TREN 20 TRIEU
## 71 2 TU 10-20 TRIEU
## 72 3 TU 10-20 TRIEU
## 73 3 TU 10-20 TRIEU
## 74 4 TU 10-20 TRIEU
## 75 3 TREN 20 TRIEU
## 76 2 TU 10-20 TRIEU
## 77 4 TU 10-20 TRIEU
## 78 4 TU 10-20 TRIEU
## 79 4 TU 10-20 TRIEU
## 80 3 TREN 20 TRIEU
## 81 1 TU 10-20 TRIEU
## 82 2 TU 10-20 TRIEU
## 83 3 TU 10-20 TRIEU
## 84 3 TREN 20 TRIEU
## 85 2 TU 10-20 TRIEU
## 86 3 TREN 20 TRIEU
## 87 2 TU 10-20 TRIEU
## 88 1 TU 10-20 TRIEU
## 89 1 TREN 20 TRIEU
## 90 3 TU 10-20 TRIEU
## 91 3 TU 10-20 TRIEU
## 92 1 TREN 20 TRIEU
## 93 2 TU 10-20 TRIEU
## 94 3 TU 10-20 TRIEU
## 95 1 TREN 20 TRIEU
## 96 3 TU 10-20 TRIEU
## 97 2 TU 10-20 TRIEU
## 98 4 TREN 20 TRIEU
## 99 4 TREN 20 TRIEU
## 100 2 TU 10-20 TRIEU
## 101 2 TREN 20 TRIEU
## 102 2 TU 10-20 TRIEU
## 103 1 TREN 20 TRIEU
## 104 2 TREN 20 TRIEU
## 105 2 TU 10-20 TRIEU
## 106 1 TREN 20 TRIEU
## 107 2 TU 10-20 TRIEU
## 108 2 TREN 20 TRIEU
## 109 2 TU 10-20 TRIEU
## 110 4 TU 10-20 TRIEU
## 111 3 <10 TRIEU
## 112 2 TREN 20 TRIEU
## 113 3 TU 10-20 TRIEU
## 114 3 TU 10-20 TRIEU
## 115 4 TREN 20 TRIEU
## 116 3 TREN 20 TRIEU
## 117 2 TU 10-20 TRIEU
## 118 3 TU 10-20 TRIEU
## 119 4 TREN 20 TRIEU
## 120 3 TREN 20 TRIEU
## 121 4 TREN 20 TRIEU
## 122 3 TU 10-20 TRIEU
## 123 2 TREN 20 TRIEU
## 124 3 TU 10-20 TRIEU
## 125 4 TREN 20 TRIEU
## 126 2 TU 10-20 TRIEU
## 127 4 TU 10-20 TRIEU
## 128 3 TREN 20 TRIEU
## 129 2 TU 10-20 TRIEU
## 130 4 TREN 20 TRIEU
## 131 3 TU 10-20 TRIEU
## 132 3 TREN 20 TRIEU
## 133 2 TREN 20 TRIEU
## 134 3 TU 10-20 TRIEU
## 135 3 TREN 20 TRIEU
## 136 4 TU 10-20 TRIEU
## 137 2 <10 TRIEU
## 138 3 TREN 20 TRIEU
## 139 3 TU 10-20 TRIEU
## 140 4 TU 10-20 TRIEU
## 141 3 TREN 20 TRIEU
## 142 4 TU 10-20 TRIEU
## 143 3 TU 10-20 TRIEU
## 144 2 TREN 20 TRIEU
## 145 3 <10 TRIEU
## 146 3 <10 TRIEU
## 147 3 TU 10-20 TRIEU
## 148 4 TU 10-20 TRIEU
## 149 4 TU 10-20 TRIEU
## 150 3 TU 10-20 TRIEU
## 151 2 TU 10-20 TRIEU
## 152 1 TREN 20 TRIEU
## 153 3 TU 10-20 TRIEU
## 154 1 TREN 20 TRIEU
## 155 3 TU 10-20 TRIEU
## 156 1 TU 10-20 TRIEU
## 157 2 TREN 20 TRIEU
## 158 3 TU 10-20 TRIEU
## 159 1 TU 10-20 TRIEU
## 160 2 TREN 20 TRIEU
## 161 3 TU 10-20 TRIEU
## 162 3 <10 TRIEU
## 163 1 TREN 20 TRIEU
## 164 3 TU 10-20 TRIEU
## 165 2 TU 10-20 TRIEU
## 166 2 TREN 20 TRIEU
## 167 3 TU 10-20 TRIEU
## 168 3 <10 TRIEU
## 169 2 TREN 20 TRIEU
## 170 4 TU 10-20 TRIEU
## 171 2 <10 TRIEU
## 172 4 TU 10-20 TRIEU
## 173 4 TU 10-20 TRIEU
## 174 1 TU 10-20 TRIEU
## 175 1 TU 10-20 TRIEU
## 176 3 TU 10-20 TRIEU
## 177 3 <10 TRIEU
## 178 1 TU 10-20 TRIEU
## 179 3 <10 TRIEU
## 180 2 TREN 20 TRIEU
## 181 2 TU 10-20 TRIEU
## 182 2 TU 10-20 TRIEU
## 183 4 TU 10-20 TRIEU
## 184 4 TU 10-20 TRIEU
## 185 3 TREN 20 TRIEU
## 186 1 TU 10-20 TRIEU
## 187 3 TU 10-20 TRIEU
## 188 1 TREN 20 TRIEU
## 189 2 TU 10-20 TRIEU
## 190 3 <10 TRIEU
## 191 1 TREN 20 TRIEU
## 192 1 TU 10-20 TRIEU
## 193 2 TU 10-20 TRIEU
## 194 1 TU 10-20 TRIEU
## 195 3 TREN 20 TRIEU
## 196 2 TU 10-20 TRIEU
## 197 4 TU 10-20 TRIEU
## 198 4 TU 10-20 TRIEU
#xac dinh nhom tuoi va thu nhap co so luong lon nhat
library(gmodels)
## Registered S3 method overwritten by 'gdata':
## method from
## reorder.factor DescTools
CrossTable(DTUOIMH,TNHAPMH)
##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 198
##
##
## | TNHAPMH
## DTUOIMH | <10 TRIEU | TREN 20 TRIEU | TU 10-20 TRIEU | Row Total |
## --------------|----------------|----------------|----------------|----------------|
## <20 TUOI | 2 | 15 | 19 | 36 |
## | 0.284 | 0.178 | 0.021 | |
## | 0.056 | 0.417 | 0.528 | 0.182 |
## | 0.125 | 0.203 | 0.176 | |
## | 0.010 | 0.076 | 0.096 | |
## --------------|----------------|----------------|----------------|----------------|
## TREN 50 TUOI | 1 | 14 | 23 | 38 |
## | 1.396 | 0.003 | 0.249 | |
## | 0.026 | 0.368 | 0.605 | 0.192 |
## | 0.062 | 0.189 | 0.213 | |
## | 0.005 | 0.071 | 0.116 | |
## --------------|----------------|----------------|----------------|----------------|
## TU 20-30 TUOI | 2 | 20 | 29 | 51 |
## | 1.092 | 0.046 | 0.050 | |
## | 0.039 | 0.392 | 0.569 | 0.258 |
## | 0.125 | 0.270 | 0.269 | |
## | 0.010 | 0.101 | 0.146 | |
## --------------|----------------|----------------|----------------|----------------|
## TU 31-50 TUOI | 11 | 25 | 37 | 73 |
## | 4.411 | 0.191 | 0.199 | |
## | 0.151 | 0.342 | 0.507 | 0.369 |
## | 0.688 | 0.338 | 0.343 | |
## | 0.056 | 0.126 | 0.187 | |
## --------------|----------------|----------------|----------------|----------------|
## Column Total | 16 | 74 | 108 | 198 |
## | 0.081 | 0.374 | 0.545 | |
## --------------|----------------|----------------|----------------|----------------|
##
##
table(DTUOIMH,TNHAPMH)
## TNHAPMH
## DTUOIMH <10 TRIEU TREN 20 TRIEU TU 10-20 TRIEU
## <20 TUOI 2 15 19
## TREN 50 TUOI 1 14 23
## TU 20-30 TUOI 2 20 29
## TU 31-50 TUOI 11 25 37
table(DTUOIMH,TNHAPMH)/ sum(table(DTUOIMH,TNHAPMH))
## TNHAPMH
## DTUOIMH <10 TRIEU TREN 20 TRIEU TU 10-20 TRIEU
## <20 TUOI 0.010101010 0.075757576 0.095959596
## TREN 50 TUOI 0.005050505 0.070707071 0.116161616
## TU 20-30 TUOI 0.010101010 0.101010101 0.146464646
## TU 31-50 TUOI 0.055555556 0.126262626 0.186868687
###NHAN XET CAU 3: nhom tuoi va nhom thu nhap co so luong quan sat lon nhat
#la tu 31-50 tuoi voi thu nhap tu 10-20 trieu;co 37 truong hop/doi tuong (18,7%)
#cau 4
library(gmodels)
CrossTable(GTINHMH,DTUOIMH)
##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 198
##
##
## | DTUOIMH
## GTINHMH | <20 TUOI | TREN 50 TUOI | TU 20-30 TUOI | TU 31-50 TUOI | Row Total |
## -------------|---------------|---------------|---------------|---------------|---------------|
## Nam | 24 | 21 | 35 | 41 | 121 |
## | 0.182 | 0.213 | 0.471 | 0.292 | |
## | 0.198 | 0.174 | 0.289 | 0.339 | 0.611 |
## | 0.667 | 0.553 | 0.686 | 0.562 | |
## | 0.121 | 0.106 | 0.177 | 0.207 | |
## -------------|---------------|---------------|---------------|---------------|---------------|
## NU | 12 | 17 | 16 | 32 | 77 |
## | 0.286 | 0.334 | 0.741 | 0.459 | |
## | 0.156 | 0.221 | 0.208 | 0.416 | 0.389 |
## | 0.333 | 0.447 | 0.314 | 0.438 | |
## | 0.061 | 0.086 | 0.081 | 0.162 | |
## -------------|---------------|---------------|---------------|---------------|---------------|
## Column Total | 36 | 38 | 51 | 73 | 198 |
## | 0.182 | 0.192 | 0.258 | 0.369 | |
## -------------|---------------|---------------|---------------|---------------|---------------|
##
##
### NHAN XET CAU 4: trong tat ca cac nhom tuoi thi gioi tinh nam deu chiem ty trong cao hon
#VE DO THI
#cau 5
pie(table(GTINHMH),col=c("lightblue","lightpink"),sub="DO THI TY LE GIOI TINH")
#cau 6
DTUOI.freq<-table(DTUOIMH)
DTUOI.freq
## DTUOIMH
## <20 TUOI TREN 50 TUOI TU 20-30 TUOI TU 31-50 TUOI
## 36 38 51 73
barplot(DTUOI.freq,xlab="Nhom tuoi",ylab="So luong", main="Bieu do cot cua cac nhom tuoi",col=c("lightgreen","lightyellow","orange","blue"))
# cau 7
hist(Ftb,col="lightpink",xlab="gia tri Ftb",border="red",ylab="tan so Ftb",main = "do thi Histogram Ftb",xlim = c(2,5),ylim=c(0,1))
lines(density(na.omit(Ftb)),col="red",lwd=2)
# NHAN XET CAU 7 :
# Ve hinh dang: Bien Ftb chua co hing dang chuong
# Su phan bo cua bien Fbt chua dat phan phoi chuan
# cau 8
boxplot(Ftb,ylab="Gia tri Ftb",col="lightgreen")
boxplot.stats(Ftb)
## $stats
## [1] 2.0 3.0 3.9 4.4 5.0
##
## $n
## [1] 198
##
## $conf
## [1] 3.7428 4.0572
##
## $out
## numeric(0)
#ket qua cho thay bien Ftb khong co gia tri ngoai nlai, vi $out numeric(0)
#cau 9
plot(Atb,Ftb,xlab="Gia tri Atb",ylab="gia tri Ftb",col="lightgreen",pch=21)
abline(lm(Ftb~Atb),col="lightpink",lwd=2)
#NHAN XET CAU 9 :
#Chieu huong: tuong quan thuan(duong),duong hoi quy di len tu trai sang phai
#Muc do tuyen tinh:yeu,vi cac diem du lieu phan tan rong quanh duong hoi quy
#cau10
library(psych)
fa=data.frame(A1,A2,A3,A4,A5)
alpha(fa)
##
## Reliability analysis
## Call: alpha(x = fa)
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
## 0.93 0.94 0.95 0.74 14 0.0083 4.1 0.72 0.78
##
## 95% confidence boundaries
## lower alpha upper
## Feldt 0.91 0.93 0.95
## Duhachek 0.92 0.93 0.95
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r med.r
## A1 0.96 0.96 0.97 0.86 25.2 0.0049 0.0057 0.87
## A2 0.90 0.91 0.91 0.71 9.7 0.0125 0.0270 0.67
## A3 0.90 0.91 0.91 0.71 9.7 0.0125 0.0270 0.67
## A4 0.91 0.92 0.92 0.73 11.1 0.0111 0.0361 0.72
## A5 0.90 0.91 0.91 0.70 9.5 0.0121 0.0277 0.67
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## A1 198 0.74 0.73 0.60 0.60 4.1 0.89
## A2 198 0.94 0.94 0.95 0.90 4.0 0.83
## A3 198 0.94 0.94 0.95 0.90 4.0 0.83
## A4 198 0.89 0.90 0.89 0.84 4.1 0.74
## A5 198 0.94 0.94 0.95 0.90 4.0 0.73
##
## Non missing response frequency for each item
## 2 3 4 5 miss
## A1 0.00 0.33 0.20 0.47 0
## A2 0.02 0.30 0.35 0.33 0
## A3 0.02 0.30 0.35 0.33 0
## A4 0.01 0.21 0.45 0.33 0
## A5 0.01 0.24 0.48 0.28 0
###nhan xet cau 10:
#GIA TRI Cronbach's Alpha = 0.93 > 0.6 ; nhu vay nhan to A dam bao do tin cay
#He so tuong quan bien tong cac bien/thang do deu > 0.3 (dat yeu cau)
# => Nen khong bat ky loai bien/thang do nao
#cau11
abcde=data.frame(A1,A2,A3,A4,A5,B1,B2,B3,B4,C1,C2,C3,C4,D1,D2,D3,E1,E2,E3,E4)
library(psych)
cortest.bartlett(abcde)
## R was not square, finding R from data
## $chisq
## [1] 5048.334
##
## $p.value
## [1] 0
##
## $df
## [1] 190
KMO(abcde)
## Kaiser-Meyer-Olkin factor adequacy
## Call: KMO(r = abcde)
## Overall MSA = 0.67
## MSA for each item =
## A1 A2 A3 A4 A5 B1 B2 B3 B4 C1 C2 C3 C4 D1 D2 D3
## 0.77 0.70 0.61 0.75 0.68 0.78 0.81 0.53 0.56 0.58 0.53 0.86 0.84 0.72 0.74 0.88
## E1 E2 E3 E4
## 0.60 0.82 0.74 0.61
###nhan xet cau 11:
#Gia tri KMO=0,67 > 0,5 :dam bao yeu cau phan tich EFA
#Gia tri Sig.(P-Value) cua Barlett's=0,000 < 5% do do ket qua EFA co the su dung de phan tich
#cau12
principal(abcde,cor=TRUE,nfactors = 20,rotate="none")
## Principal Components Analysis
## Call: principal(r = abcde, nfactors = 20, rotate = "none", cor = TRUE)
## Standardized loadings (pattern matrix) based upon correlation matrix
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11 PC12
## A1 0.45 -0.26 0.51 0.05 0.21 -0.20 -0.25 -0.52 0.11 -0.04 0.16 0.03
## A2 0.64 -0.46 0.53 0.01 -0.06 0.09 0.09 0.07 0.02 -0.08 -0.13 -0.16
## A3 0.63 -0.47 0.53 0.03 -0.05 0.10 0.10 0.07 0.03 -0.10 -0.12 -0.16
## A4 0.56 -0.56 0.46 0.00 0.03 0.03 0.04 0.08 -0.07 0.13 0.10 0.27
## A5 0.65 -0.53 0.44 0.02 0.00 -0.06 0.11 0.16 -0.06 0.02 0.02 0.13
## B1 0.54 0.16 -0.43 0.61 0.06 0.24 -0.07 -0.02 0.08 0.00 -0.05 0.07
## B2 0.45 0.27 -0.27 0.44 0.13 -0.52 0.18 0.13 -0.24 0.03 0.18 -0.09
## B3 0.61 0.19 -0.46 0.59 0.07 0.04 0.01 0.00 0.00 -0.05 0.00 0.02
## B4 0.57 0.15 -0.41 0.61 0.08 0.24 -0.03 -0.08 0.04 0.00 -0.02 -0.03
## C1 0.51 0.59 0.03 -0.50 0.21 0.16 -0.09 0.13 -0.11 0.04 0.11 -0.11
## C2 0.44 0.52 0.09 -0.52 0.27 0.28 -0.13 0.06 -0.07 0.14 0.20 -0.01
## C3 0.38 0.64 -0.02 -0.27 0.23 -0.22 0.15 0.07 0.30 0.15 -0.27 0.22
## C4 0.48 0.57 0.08 -0.35 0.26 -0.17 0.09 -0.09 0.07 -0.26 -0.09 -0.13
## D1 0.40 0.44 -0.01 -0.13 -0.61 -0.08 -0.19 0.19 0.18 -0.29 0.20 0.12
## D2 0.53 0.33 0.08 -0.02 -0.59 -0.13 -0.11 -0.12 0.03 0.39 -0.07 -0.17
## D3 0.17 0.67 0.17 -0.15 -0.32 0.14 0.26 -0.30 -0.36 -0.11 -0.12 0.17
## E1 -0.29 0.49 0.66 0.43 0.08 -0.02 -0.15 0.08 -0.06 0.00 -0.04 0.02
## E2 -0.34 0.40 0.45 0.29 -0.05 0.16 0.50 -0.08 0.25 0.07 0.28 -0.06
## E3 -0.27 0.50 0.68 0.40 0.03 0.00 -0.12 0.10 -0.01 -0.04 -0.10 -0.05
## E4 -0.30 0.48 0.66 0.42 0.08 -0.01 -0.17 0.07 -0.05 0.03 -0.02 0.05
## PC13 PC14 PC15 PC16 PC17 PC18 PC19 PC20 h2 u2 com
## A1 -0.11 0.01 -0.01 0.00 0.01 -0.01 0.00 0.00 1 0.0e+00 5.2
## A2 -0.10 -0.05 0.03 -0.07 0.06 0.06 -0.01 -0.02 1 0.0e+00 3.4
## A3 -0.10 0.04 0.05 0.09 -0.06 -0.02 0.02 0.03 1 -8.9e-16 3.5
## A4 0.20 -0.06 0.07 0.06 0.05 0.00 -0.02 0.00 1 0.0e+00 4.1
## A5 0.04 0.06 -0.14 -0.07 -0.05 -0.04 0.01 -0.01 1 -1.6e-15 3.3
## B1 0.04 0.19 0.04 0.00 0.05 0.01 0.01 0.00 1 2.2e-16 3.8
## B2 -0.08 0.02 0.07 -0.01 0.00 0.00 0.00 0.00 1 5.6e-16 5.8
## B3 -0.02 -0.07 -0.14 0.04 -0.01 0.05 -0.03 0.02 1 1.2e-15 3.3
## B4 0.02 -0.13 0.06 -0.03 -0.05 -0.05 0.01 -0.02 1 8.9e-16 3.5
## C1 -0.07 -0.04 -0.07 0.05 0.09 -0.03 0.04 -0.01 1 1.4e-15 4.1
## C2 -0.04 0.04 0.05 -0.04 -0.07 0.03 -0.04 0.01 1 7.8e-16 5.0
## C3 -0.14 -0.02 0.02 0.00 0.00 0.00 0.00 0.00 1 1.2e-15 4.7
## C4 0.33 0.01 0.00 -0.01 -0.01 0.00 0.00 0.00 1 1.1e-15 5.1
## D1 -0.05 -0.01 0.02 0.00 0.00 0.00 0.00 0.00 1 1.3e-15 4.6
## D2 0.11 0.01 -0.02 0.00 0.00 0.00 0.00 0.00 1 1.6e-15 4.1
## D3 -0.07 0.01 0.01 0.00 0.00 0.00 0.00 0.00 1 1.7e-15 4.1
## E1 0.02 0.01 -0.01 0.07 -0.05 0.04 0.02 -0.05 1 1.1e-16 3.4
## E2 0.01 0.00 -0.02 0.00 0.01 0.00 0.00 0.00 1 6.7e-16 6.2
## E3 -0.03 0.02 -0.01 0.00 0.04 -0.06 -0.07 0.00 1 3.3e-16 3.2
## E4 0.05 -0.05 0.02 -0.07 0.01 0.01 0.04 0.05 1 -2.2e-16 3.5
##
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11
## SS loadings 4.59 4.23 3.45 2.65 1.17 0.71 0.62 0.54 0.43 0.41 0.39
## Proportion Var 0.23 0.21 0.17 0.13 0.06 0.04 0.03 0.03 0.02 0.02 0.02
## Cumulative Var 0.23 0.44 0.61 0.75 0.80 0.84 0.87 0.90 0.92 0.94 0.96
## Proportion Explained 0.23 0.21 0.17 0.13 0.06 0.04 0.03 0.03 0.02 0.02 0.02
## Cumulative Proportion 0.23 0.44 0.61 0.75 0.80 0.84 0.87 0.90 0.92 0.94 0.96
## PC12 PC13 PC14 PC15 PC16 PC17 PC18 PC19 PC20
## SS loadings 0.31 0.24 0.08 0.07 0.04 0.03 0.02 0.01 0.01
## Proportion Var 0.02 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## Cumulative Var 0.98 0.99 0.99 0.99 1.00 1.00 1.00 1.00 1.00
## Proportion Explained 0.02 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## Cumulative Proportion 0.98 0.99 0.99 0.99 1.00 1.00 1.00 1.00 1.00
##
## Mean item complexity = 4.2
## Test of the hypothesis that 20 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0
## with the empirical chi square 0 with prob < NA
##
## Fit based upon off diagonal values = 1
principal(abcde,cor=TRUE,nfactors = 5,rotate="varimax")
## Principal Components Analysis
## Call: principal(r = abcde, nfactors = 5, rotate = "varimax", cor = TRUE)
## Standardized loadings (pattern matrix) based upon correlation matrix
## RC1 RC3 RC4 RC2 RC5 h2 u2 com
## A1 0.72 0.12 0.03 0.13 -0.12 0.57 0.430 1.2
## A2 0.94 -0.05 0.02 0.00 0.12 0.90 0.099 1.0
## A3 0.94 -0.04 0.02 -0.02 0.10 0.90 0.103 1.0
## A4 0.90 -0.12 -0.01 -0.06 -0.03 0.83 0.169 1.0
## A5 0.94 -0.14 0.06 -0.02 0.04 0.90 0.095 1.1
## B1 0.02 -0.07 0.93 0.01 0.08 0.88 0.121 1.0
## B2 0.00 0.03 0.73 0.16 0.05 0.56 0.437 1.1
## B3 0.03 -0.11 0.97 0.06 0.10 0.96 0.036 1.1
## B4 0.06 -0.08 0.94 0.02 0.08 0.90 0.099 1.0
## C1 0.03 -0.06 0.04 0.92 0.21 0.89 0.110 1.1
## C2 0.06 -0.04 -0.04 0.90 0.12 0.82 0.176 1.1
## C3 -0.09 0.07 0.16 0.78 0.14 0.68 0.323 1.2
## C4 0.05 0.04 0.11 0.84 0.14 0.75 0.251 1.1
## D1 -0.01 -0.02 0.11 0.24 0.82 0.74 0.256 1.2
## D2 0.18 0.01 0.21 0.19 0.80 0.76 0.245 1.4
## D3 -0.15 0.29 -0.01 0.43 0.58 0.63 0.368 2.6
## E1 -0.01 0.98 -0.02 0.03 0.00 0.95 0.047 1.0
## E2 -0.14 0.73 -0.09 -0.04 0.07 0.56 0.440 1.1
## E3 0.01 0.97 -0.04 0.04 0.05 0.95 0.048 1.0
## E4 -0.02 0.97 -0.04 0.03 -0.01 0.94 0.055 1.0
##
## RC1 RC3 RC4 RC2 RC5
## SS loadings 4.08 3.54 3.34 3.30 1.83
## Proportion Var 0.20 0.18 0.17 0.17 0.09
## Cumulative Var 0.20 0.38 0.55 0.71 0.80
## Proportion Explained 0.25 0.22 0.21 0.21 0.11
## Cumulative Proportion 0.25 0.47 0.68 0.89 1.00
##
## Mean item complexity = 1.2
## Test of the hypothesis that 5 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0.03
## with the empirical chi square 71.75 with prob < 0.99
##
## Fit based upon off diagonal values = 0.99
###nhan xet cau 12:
# So nhan to duoc trich : 5 nhom nhan to
# Gia tri Eigenvalue = 1,83 > 1 (dat yeu cau)
# Gia tri tong phuong sai trich = 0.80 = 80% > 50% (dat yeu cau)
# Cau truc nhan to co phu hop voi du lieu ban dau vi cac bien/thang do sap xep theo dung nhom nhan to
#cau 13:
library(psych)
vars=cbind(Atb,Btb,Ctb,Dtb,Etb,Ftb)
pairs.panels(vars)
library(Hmisc)
##
## Attaching package: 'Hmisc'
## The following objects are masked from 'package:DescTools':
##
## %nin%, Label, Mean, Quantile
## The following object is masked from 'package:psych':
##
## describe
## The following objects are masked from 'package:base':
##
## format.pval, units
result=rcorr(as.matrix(vars),type="pearson")
result$r
## Atb Btb Ctb Dtb Etb Ftb
## Atb 1.00000000 0.06221638 0.03185639 0.04014488 -0.08600054 0.2222299
## Btb 0.06221638 1.00000000 0.16097635 0.22801725 -0.10776531 0.2511952
## Ctb 0.03185639 0.16097635 1.00000000 0.50335736 0.02399959 0.5915879
## Dtb 0.04014488 0.22801725 0.50335736 1.00000000 0.13044247 0.5733869
## Etb -0.08600054 -0.10776531 0.02399959 0.13044247 1.00000000 0.2096923
## Ftb 0.22222985 0.25119517 0.59158791 0.57338686 0.20969230 1.0000000
result$P
## Atb Btb Ctb Dtb Etb Ftb
## Atb NA 0.3838835582 6.559338e-01 5.744306e-01 0.228316785 0.0016512737
## Btb 0.383883558 NA 2.347636e-02 1.234270e-03 0.130738634 0.0003574484
## Ctb 0.655933822 0.0234763641 NA 4.085621e-14 0.737161764 0.0000000000
## Dtb 0.574430580 0.0012342702 4.085621e-14 NA 0.066996016 0.0000000000
## Etb 0.228316785 0.1307386340 7.371618e-01 6.699602e-02 NA 0.0030269715
## Ftb 0.001651274 0.0003574484 0.000000e+00 0.000000e+00 0.003026971 NA
###nhan xet cau 13:
#Bien Ftb co moi tuong quan duong voi Atb,Btb,Ctb,Dtb,Etb vi he so tuong quan Pearson cua cac moi quan he nay > 0
#Moi tuong quan giua Ftb va cac bien Atb,Btb,Ctb,Dtb,Etb co y nghia thong ke vi gia tri Sig.(p-value) cua cac moi quan he nay nho hon 5%