BÀI TẬP PTDLĐT
Thế Thị Hoài Ngọc
2023-06-13
#Thư viện sử dụng
library(AER)## Warning: package 'AER' was built under R version 4.3.1## Loading required package: car## Warning: package 'car' was built under R version 4.3.1## Loading required package: carData## Warning: package 'carData' was built under R version 4.3.1## Loading required package: lmtest## Warning: package 'lmtest' was built under R version 4.3.1## Loading required package: zoo## Warning: package 'zoo' was built under R version 4.3.1##
## Attaching package: 'zoo'## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric## Loading required package: sandwich## Warning: package 'sandwich' was built under R version 4.3.1## Loading required package: survivallibrary(DescTools)## Warning: package 'DescTools' was built under R version 4.3.1##
## Attaching package: 'DescTools'## The following object is masked from 'package:car':
##
## Recodelibrary(ggplot2)## Warning: package 'ggplot2' was built under R version 4.3.1setwd("D:/HN")
bank <- read.csv("databank.csv", header=TRUE)
str(bank)## 'data.frame': 2000 obs. of 11 variables:
## $ ID : int 1 2 3 4 5 6 7 8 9 10 ...
## $ age : int 50 41 36 31 51 27 27 59 43 46 ...
## $ job : chr "management" "technician" "entrepreneur" "blue-collar" ...
## $ marital : int 1 2 1 0 0 2 1 0 1 2 ...
## $ education : chr "secondary" "secondary" "secondary" "tertiary" ...
## $ default : int 0 0 0 0 0 0 0 0 0 0 ...
## $ balance : int -111 -329 904 106 300 245 494 1774 1063 -191 ...
## $ housing : int 1 0 0 1 0 1 0 0 1 1 ...
## $ duration : int 19 13 36 67 8 7 16 14 141 674 ...
## $ previous : int 11 8 9 2 6 7 10 9 3 3 ...
## $ term_deposit: int 0 0 0 0 0 0 0 0 0 0 ...1 BTVN TUẦN 6
1.1 Mô hình hồi quy với biến phụ thuộc term_deposit và các biến độc lập age, marital, education, housing và duration
1.1.1 Mô hình logit
bank$term_deposit <- as.factor(bank$term_deposit)var1 <- glm((term_deposit) ~ age + marital + education + housing + duration, family = binomial(link = "logit"), data = bank)
summary(var1)##
## Call:
## glm(formula = (term_deposit) ~ age + marital + education + housing +
## duration, family = binomial(link = "logit"), data = bank)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.3314054 0.3403227 -6.851 7.36e-12 ***
## age 0.0098944 0.0049335 2.006 0.0449 *
## marital -0.1187792 0.0880562 -1.349 0.1774
## educationsecondary 0.5532293 0.2200505 2.514 0.0119 *
## educationtertiary 1.1300527 0.2256798 5.007 5.52e-07 ***
## educationunknown 0.1955033 0.3771572 0.518 0.6042
## housing -1.3713787 0.1290120 -10.630 < 2e-16 ***
## duration 0.0024103 0.0002196 10.977 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 2050.5 on 1999 degrees of freedom
## Residual deviance: 1769.2 on 1992 degrees of freedom
## AIC: 1785.2
##
## Number of Fisher Scoring iterations: 51.1.2 Mô hình probit
Mô hình probit có dạng tổng quát:
\(\pi(x) = \phi(\alpha + \beta x)\)
var2 <- glm((term_deposit) ~ age + marital + education + housing + duration, family = binomial(link = "probit"), data = bank)
summary(var2)##
## Call:
## glm(formula = (term_deposit) ~ age + marital + education + housing +
## duration, family = binomial(link = "probit"), data = bank)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.3522427 0.1920361 -7.042 1.90e-12 ***
## age 0.0055180 0.0028697 1.923 0.05449 .
## marital -0.0701871 0.0501669 -1.399 0.16179
## educationsecondary 0.3238634 0.1208113 2.681 0.00735 **
## educationtertiary 0.6508269 0.1248218 5.214 1.85e-07 ***
## educationunknown 0.0992287 0.2083178 0.476 0.63384
## housing -0.7727402 0.0709043 -10.898 < 2e-16 ***
## duration 0.0013255 0.0001245 10.650 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 2050.5 on 1999 degrees of freedom
## Residual deviance: 1769.1 on 1992 degrees of freedom
## AIC: 1785.1
##
## Number of Fisher Scoring iterations: 51.1.3 Mô hình cloglog
Mô hình tổng quát của Cloglog:
\(Cloglog(π)=log(−log(1−π))=β_0+β_1X_1+β_2X_2+⋯+β_kX_k)\)
var3 <- glm((term_deposit) ~ age + marital + education + housing + duration, family = binomial(link = "cloglog"), data = bank)## Warning: glm.fit: algorithm did not convergesummary(var3)##
## Call:
## glm(formula = (term_deposit) ~ age + marital + education + housing +
## duration, family = binomial(link = "cloglog"), data = bank)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.0902338 0.2821102 -7.409 1.27e-13 ***
## age 0.0066938 0.0040676 1.646 0.0998 .
## marital -0.0911241 0.0733740 -1.242 0.2143
## educationsecondary 0.4507911 0.1910385 2.360 0.0183 *
## educationtertiary 0.8684676 0.1943208 4.469 7.85e-06 ***
## educationunknown 0.1326228 0.3340395 0.397 0.6913
## housing -1.1190068 0.1079202 -10.369 < 2e-16 ***
## duration 0.0015225 0.0001418 10.734 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 2050.5 on 1999 degrees of freedom
## Residual deviance: 1803.1 on 1992 degrees of freedom
## AIC: 1819.1
##
## Number of Fisher Scoring iterations: 251.2 Lựa chọn mô hình
1.2.1 Chỉ số AIC
AIC(logit) = 1785.2
AIC(probit) = 1785.1
AIC(cloglog) = 1819.1
Mô hình probit có AIC nhỏ nhất nên ta chọn MH probit
1.2.2 Deviance
Deviance(logit) = 1769.2
Deviance(probit) = 1769.1
Deviance(cloglog) = 1803.1
Mô hình probit có deviance nhỏ nhất nên ta chọn MH probit
1.2.3 Brier Score
library(DescTools)
j1 <- BrierScore(var1)
j1## [1] 0.1411042library(DescTools)
j2 <- BrierScore(var2)
j2## [1] 0.1412038library(DescTools)
j3 <- BrierScore(var3)
j3## [1] 0.1429177Dựa vào tiêu chí Brier score ta thấy MH logit có giá trị nhỏ nhất (0.1411042) nên ta chọn MH logit
1.2.4 Ma trận nhầm lẫn
1.2.4.1 Mô hình logit
library(caret)## Warning: package 'caret' was built under R version 4.3.1## Loading required package: lattice##
## Attaching package: 'caret'## The following objects are masked from 'package:DescTools':
##
## MAE, RMSE## The following object is masked from 'package:survival':
##
## clusterbank$term_deposit <- bank$term_deposit
predictions <- predict(var1, newdata = bank, type = "response")
predicted_classes <- ifelse(predictions > 0.5, "1", "0")
predictions1<-factor(predicted_classes, levels = c("0","1"))
actual<- factor(bank$term_deposit, labels = c("0","1"))
confusionMatrix(table(predictions1, actual))## Confusion Matrix and Statistics
##
## actual
## predictions1 0 1
## 0 1544 361
## 1 38 57
##
## Accuracy : 0.8005
## 95% CI : (0.7823, 0.8178)
## No Information Rate : 0.791
## P-Value [Acc > NIR] : 0.1544
##
## Kappa : 0.157
##
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.9760
## Specificity : 0.1364
## Pos Pred Value : 0.8105
## Neg Pred Value : 0.6000
## Prevalence : 0.7910
## Detection Rate : 0.7720
## Detection Prevalence : 0.9525
## Balanced Accuracy : 0.5562
##
## 'Positive' Class : 0
## Mô hình có logit có độ chính xác toàn thể là 80.05%, độ nhạy là 97.60% và độ đặc hiệu là 13.64%
1.2.4.2 Mô hình probit
library(caret)
bank$term_deposit <- bank$term_deposit
predictions <- predict(var2, newdata = bank, type = "response")
predicted_classes <- ifelse(predictions > 0.5, "1", "0")
predictions1<-factor(predicted_classes, levels = c("0","1"))
actual<- factor(bank$term_deposit, labels = c("0","1"))
confusionMatrix(table(predictions1, actual))## Confusion Matrix and Statistics
##
## actual
## predictions1 0 1
## 0 1548 366
## 1 34 52
##
## Accuracy : 0.8
## 95% CI : (0.7818, 0.8173)
## No Information Rate : 0.791
## P-Value [Acc > NIR] : 0.168
##
## Kappa : 0.1454
##
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.9785
## Specificity : 0.1244
## Pos Pred Value : 0.8088
## Neg Pred Value : 0.6047
## Prevalence : 0.7910
## Detection Rate : 0.7740
## Detection Prevalence : 0.9570
## Balanced Accuracy : 0.5515
##
## 'Positive' Class : 0
## Mô hình có probit có độ chính xác toàn thể là 80%, độ nhạy là 97.85% và độ đặc hiệu là 12.44%
1.2.4.3 Mô hình cloglog
library(caret)
bank$term_deposit <- bank$term_deposit
predictions <- predict(var3, newdata = bank, type = "response")
predicted_classes <- ifelse(predictions > 0.5, "1", "0")
predictions1<-factor(predicted_classes, levels = c("0","1"))
actual<- factor(bank$term_deposit, labels = c("0","1"))
confusionMatrix(table(predictions1, actual))## Confusion Matrix and Statistics
##
## actual
## predictions1 0 1
## 0 1559 381
## 1 23 37
##
## Accuracy : 0.798
## 95% CI : (0.7797, 0.8154)
## No Information Rate : 0.791
## P-Value [Acc > NIR] : 0.2296
##
## Kappa : 0.108
##
## Mcnemar's Test P-Value : <2e-16
##
## Sensitivity : 0.98546
## Specificity : 0.08852
## Pos Pred Value : 0.80361
## Neg Pred Value : 0.61667
## Prevalence : 0.79100
## Detection Rate : 0.77950
## Detection Prevalence : 0.97000
## Balanced Accuracy : 0.53699
##
## 'Positive' Class : 0
## Mô hình có probit có độ chính xác toàn thể là 79.8%, độ nhạy là 98.55% và độ đặc hiệu là 8.85%
1.2.5 Kết luận
AIC <- c(1785.2, 1785.1, 1819.1)
Brierscore <- c(0.1411042,0.1412038,0.1429177)
Deviance <- c( 1769.2, 1769.1, 1803.1)
confusionMatrix <- c( 0.8005 ,0.8 ,0.798)
MH <- c('logit','probit','cloglog')
KetQua <- data.frame(MH, confusionMatrix, Deviance, Brierscore, AIC)
KetQua## MH confusionMatrix Deviance Brierscore AIC
## 1 logit 0.8005 1769.2 0.1411042 1785.2
## 2 probit 0.8000 1769.1 0.1412038 1785.1
## 3 cloglog 0.7980 1803.1 0.1429177 1819.1Ta thấy, Mô hình logit và Probit đều thỏa 2/4 chỉ tiêu, vì vậy ta tiến hành xét chỉ tiêu phụ là độ đặc hiệu. Độ đặc hiệu của MH logit = 13.64% lớn hơn MH probit = 12.44%. Vì vậy, Mô hình được chọn và phù hợp nhất là MH logit.
1.2.6 Giải thích mô hình
Kết quả phân tích hồi quy logit cho thấy, với 9 biến đưa vào mô hình hồi quy để phân tích nhưng kết quả cho thấy có 5 biến liên quan đến biến term_deposit, và chỉ có 3/5 biến độc lập đó có ý nghĩa thống kê bao gồm:
age: độ tuổi
housing: tình trạng nhà ở
duration: thời lượng cuộc gọi
Với giả thuyết các yếu tố khác không đổi, ảnh hưởng của từng biến đến được diễn giải như sau:
Ở mức ý nghĩa 1%, độ tuổi tác động tích cực lên quyết định đăng kí mở tài khoản của khách hàng.
Ở mức ý nghĩa 1%, tình trạng nhà ở tác động tiêu cực lên quyết định đăng kí mở tài khoản của khách hàng.
Ở mức ý nghĩa 1%, thời lượng cuộc gọi tác động tích cực lên quyết định đăng kí mở tài khoản của khách hàng.
2 BTVN TUẦN 5: Kiểm định tính độc lập cho các cặp biến
2.0.1 Độ tuổi (age) và quyết định đăng kí mở tài khoản (term_deposit)
Giả thuyết:
H0: Độ tuổi (age) và quyết định đăng kí mở tài khoản (term_deposit) độc lập với nhau
H1: Độ tuổi (age) và quyết định đăng kí mở tài khoản (term_deposit) không độc lập với nhau
gt1 <- table(bank$age, bank$term_deposit)
gt1##
## 0 1
## 19 4 2
## 20 3 2
## 21 2 3
## 22 2 4
## 23 6 4
## 24 12 6
## 25 13 9
## 26 37 13
## 27 45 12
## 28 42 16
## 29 55 14
## 30 63 19
## 31 71 16
## 32 63 20
## 33 81 20
## 34 66 15
## 35 79 12
## 36 82 12
## 37 62 19
## 38 57 8
## 39 53 10
## 40 57 6
## 41 53 10
## 42 40 9
## 43 39 7
## 44 37 13
## 45 37 2
## 46 30 11
## 47 27 10
## 48 31 5
## 49 26 4
## 50 28 5
## 51 15 7
## 52 21 2
## 53 20 6
## 54 30 6
## 55 16 3
## 56 26 3
## 57 29 5
## 58 23 5
## 59 26 4
## 60 10 5
## 61 8 6
## 62 2 7
## 63 6 2
## 64 5 2
## 65 3 5
## 66 3 3
## 67 3 2
## 68 4 2
## 69 2 2
## 70 3 2
## 71 3 3
## 72 2 1
## 73 1 4
## 74 2 1
## 75 2 1
## 76 1 2
## 77 1 2
## 78 4 1
## 79 0 1
## 80 2 0
## 82 2 0
## 83 2 2
## 85 0 2
## 86 1 0
## 90 0 1
## 94 1 0chisq.test(gt1)## Warning in chisq.test(gt1): Chi-squared approximation may be incorrect##
## Pearson's Chi-squared test
##
## data: gt1
## X-squared = 145.18, df = 67, p-value = 1.058e-07Ta có p_value = 1.058e-07 < 0.05 nên ta bác bỏ giả thuyết H0. Nghĩa là, độ tuổi (age) và quyết định đăng kí mở tài khoản (term_deposit) liên quan với nhau
2.0.2 Công việc (job) và quyết định đăng kí mở tài khoản (term_deposit)
Giả thuyết:
H0: Công việc (job) và quyết định đăng kí mở tài khoản (term_deposit) độc lập với nhau
H1: Công việc (job) và quyết định đăng kí mở tài khoản (term_deposit) không độc lập với nhau
gt2 <- table(bank$job, bank$term_deposit)
gt2##
## 0 1
## admin. 202 50
## blue-collar 534 141
## entrepreneur 41 15
## housemaid 13 8
## management 225 53
## retired 50 12
## self-employed 41 7
## services 185 56
## student 21 6
## technician 232 54
## unemployed 35 13
## unknown 3 3chisq.test(gt2)## Warning in chisq.test(gt2): Chi-squared approximation may be incorrect##
## Pearson's Chi-squared test
##
## data: gt2
## X-squared = 12.628, df = 11, p-value = 0.3184Ta có p_value = 0.3184 > 0.05 nên ta chưa đủ cơ sở để bác bỏ giả thuyết H0. Nghĩa là, công việc (job) và quyết định đăng kí mở tài khoản (term_deposit) độc lập với nhau
2.0.3 Tình trạng hôn nhân (marital) và quyết định đăng kí mở tài khoản (term_deposit)
Giả thuyết:
H0: Tình trạng hôn nhân (marital) và quyết định đăng kí mở tài khoản (term_deposit) độc lập với nhau
H1: Tình trạng hôn nhân (marital) và quyết định đăng kí mở tài khoản (term_deposit) không độc lập với nhau
gt3 <- table(bank$marital, bank$term_deposit)
gt3##
## 0 1
## 0 169 46
## 1 524 169
## 2 889 203chisq.test(gt3)##
## Pearson's Chi-squared test
##
## data: gt3
## X-squared = 8.6536, df = 2, p-value = 0.01321Ta có p_value = 0.01321 < 0.05 nên ta bác bỏ giả thuyết H0. Nghĩa là, Tình trạng hôn nhân (marital) và quyết định đăng kí mở tài khoản (term_deposit) liên quan với nhau
2.0.4 Trình độ học vấn (education) và quyết định đăng kí mở tài khoản (term_deposit)
Giả thuyết:
H0: Trình độ học vấn (education) và quyết định đăng kí mở tài khoản (term_deposit) độc lập với nhau
H1: Trình độ học vấn (education) và quyết định đăng kí mở tài khoản (term_deposit) không độc lập với nhau
gt4 <- table(bank$education, bank$term_deposit)
gt4##
## 0 1
## primary 220 33
## secondary 838 189
## tertiary 456 184
## unknown 68 12chisq.test(gt4)##
## Pearson's Chi-squared test
##
## data: gt4
## X-squared = 38.86, df = 3, p-value = 1.859e-08Ta có p_value = 1.859e-08 < 0.05 nên bác bỏ giả thuyết H0. Nghĩa là, Trình độ học vấn (education) và quyết định đăng kí mở tài khoản (term_deposit) liên quan với nhau
2.0.5 Tình trạng tín dụng (default) và quyết định đăng kí mở tài khoản (term_deposit)
Giả thuyết:
H0: Tình trạng tín dụng (default) và quyết định đăng kí mở tài khoản (term_deposit) độc lập với nhau
H1: Tình trạng tín dụng (default) và quyết định đăng kí mở tài khoản (term_deposit) không độc lập với nhau
gt5 <- table(bank$default, bank$term_deposit)
gt5##
## 0 1
## 0 1569 417
## 1 13 1chisq.test(gt5)## Warning in chisq.test(gt5): Chi-squared approximation may be incorrect##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: gt5
## X-squared = 0.88479, df = 1, p-value = 0.3469Ta có p_value = 0.3469 > 0.05 nên ta chưa đủ cơ sở để bác bỏ giả thuyết H0. Nghĩa là, Tình trạng tín dụng (default) và quyết định đăng kí mở tài khoản (term_deposit) độc lập với nhau
2.0.6 Số dư tài khoản (balance) và quyết định đăng kí mở tài khoản (term_deposit)
Giả thuyết:
H0: Số dư tài khoản (balance) và quyết định đăng kí mở tài khoản (term_deposit) độc lập với nhau
H1: Số dư tài khoản (balance) và quyết định đăng kí mở tài khoản (term_deposit) không độc lập với nhau
gt6 <- table(bank$balance, bank$term_deposit)
gt6##
## 0 1
## -2712 1 0
## -1455 1 0
## -932 1 0
## -898 1 0
## -812 1 0
## -675 0 1
## -670 1 0
## -665 1 0
## -613 1 0
## -550 1 0
## -547 1 0
## -538 1 0
## -522 0 1
## -521 1 0
## -491 1 0
## -464 1 0
## -462 1 0
## -456 1 0
## -435 1 0
## -421 1 0
## -417 1 0
## -398 1 0
## -393 1 0
## -382 1 0
## -378 1 0
## -376 1 0
## -359 1 0
## -329 2 0
## -321 1 0
## -318 1 0
## -312 1 0
## -292 1 0
## -277 1 0
## -254 1 0
## -253 0 1
## -251 1 0
## -220 1 0
## -212 1 0
## -210 1 0
## -197 1 0
## -194 1 0
## -191 1 0
## -187 1 0
## -158 1 0
## -152 1 0
## -151 1 0
## -149 1 0
## -145 1 0
## -130 0 1
## -125 1 0
## -121 1 0
## -117 1 0
## -111 1 0
## -101 1 0
## -100 1 0
## -97 1 0
## -93 1 0
## -91 1 0
## -85 1 0
## -84 1 0
## -73 1 0
## -68 1 0
## -61 0 1
## -60 1 0
## -57 1 0
## -56 1 0
## -55 1 0
## -54 1 0
## -53 0 1
## -43 1 0
## -41 1 1
## -39 0 1
## -34 0 1
## -30 1 0
## -28 1 0
## -19 1 0
## -17 1 0
## -5 1 0
## -3 0 1
## -2 1 0
## -1 2 0
## 0 100 22
## 1 5 1
## 2 2 2
## 3 2 2
## 4 3 0
## 5 5 0
## 6 1 1
## 8 1 0
## 9 1 0
## 10 2 0
## 11 4 0
## 12 1 0
## 13 0 1
## 15 1 0
## 16 2 1
## 18 2 0
## 19 0 1
## 20 2 0
## 21 5 0
## 23 3 0
## 24 1 0
## 25 2 2
## 26 3 1
## 27 1 0
## 28 1 0
## 29 1 0
## 31 2 1
## 32 1 0
## 33 1 2
## 34 1 0
## 35 2 0
## 36 1 0
## 37 1 0
## 39 1 0
## 40 1 1
## 42 2 1
## 43 2 0
## 45 1 0
## 46 2 1
## 47 1 0
## 48 2 0
## 49 1 0
## 51 1 0
## 52 2 1
## 53 2 0
## 54 2 0
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## 8860 1 0
## 8866 0 1
## 8929 0 1
## 9324 1 0
## 9329 1 0
## 9601 0 1
## 9610 1 0
## 9676 0 1
## 10005 1 0
## 10045 1 0
## 10152 1 0
## 10180 0 1
## 10185 0 1
## 10200 1 0
## 10469 1 0
## 10600 1 0
## 10768 1 0
## 11066 1 0
## 11174 0 1
## 11385 0 1
## 11387 1 0
## 11555 1 0
## 11767 1 0
## 11862 0 1
## 11891 0 1
## 12039 0 1
## 12048 1 0
## 12114 0 1
## 12159 1 0
## 12857 0 1
## 12926 1 0
## 13408 1 0
## 13654 1 0
## 13669 1 0
## 13849 1 0
## 13874 1 0
## 14344 1 0
## 14850 1 0
## 15261 1 0
## 15459 0 1
## 15485 0 1
## 16649 1 0
## 17441 1 0
## 17609 1 0
## 19102 1 0
## 20727 1 0
## 20806 0 1
## 21446 1 0
## 23663 1 0
## 23878 0 1
## 26306 1 0
## 26721 1 0
## 26831 1 0
## 32685 0 1chisq.test(gt6)## Warning in chisq.test(gt6): Chi-squared approximation may be incorrect##
## Pearson's Chi-squared test
##
## data: gt6
## X-squared = 1464.7, df = 1411, p-value = 0.1562Ta có p_value = 0.1562 > 0.05 nên ta chưa đủ cơ sở để bác bỏ giả thuyết H0. Nghĩa là, Số dư tài khoản (balance) và quyết định đăng kí mở tài khoản (term_deposit) độc lập với nhau
2.0.7 Tình trạng nhà ở (housing) và quyết định đăng kí mở tài khoản (term_deposit)
Giả thuyết:
H0: Tình trạng nhà ở (housing) và quyết định đăng kí mở tài khoản (term_deposit) độc lập với nhau
H1: Tình trạng nhà ở (housing) và quyết định đăng kí mở tài khoản (term_deposit) không độc lập với nhau
gt7 <- table(bank$housing, bank$term_deposit)
gt7##
## 0 1
## 0 611 275
## 1 971 143chisq.test(gt7)##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: gt7
## X-squared = 97.801, df = 1, p-value < 2.2e-16Ta có p_value = 2.2e-16 < 0.05 nên ta bác bỏ giả thuyết H0. Nghĩa là, Tình trạng nhà ở (housing) và quyết định đăng kí mở tài khoản (term_deposit) liên quan với nhau
2.0.8 Thời lượng cuộc gọi (duration) và quyết định đăng kí mở tài khoản (term_deposit)
Giả thuyết:
H0: Thời lượng cuộc gọi (duration) và quyết định đăng kí mở tài khoản (term_deposit) độc lập với nhau
H1: Thời lượng cuộc gọi (duration) và quyết định đăng kí mở tài khoản (term_deposit) không độc lập với nhau
gt8 <- table(bank$duration, bank$term_deposit)
gt8##
## 0 1
## 1 1 0
## 2 1 0
## 7 4 0
## 8 5 0
## 9 2 0
## 10 1 0
## 11 4 0
## 12 7 0
## 13 8 0
## 14 3 0
## 15 9 0
## 16 4 0
## 17 5 0
## 18 4 0
## 19 2 0
## 20 1 0
## 21 1 0
## 22 2 0
## 23 2 0
## 24 2 0
## 25 3 0
## 26 2 0
## 27 2 0
## 28 1 0
## 29 3 0
## 30 3 0
## 32 1 0
## 33 3 0
## 34 2 0
## 35 4 0
## 36 5 0
## 37 4 0
## 38 3 0
## 39 5 0
## 40 3 0
## 41 6 0
## 42 2 0
## 43 6 0
## 44 8 0
## 45 5 0
## 46 3 0
## 47 6 0
## 48 7 0
## 49 5 1
## 51 3 0
## 52 3 0
## 53 3 0
## 54 3 0
## 55 3 0
## 56 7 0
## 57 3 0
## 58 11 0
## 59 6 0
## 60 6 0
## 61 9 0
## 62 2 0
## 63 1 1
## 64 3 0
## 65 3 1
## 66 6 0
## 67 5 0
## 68 3 0
## 69 4 0
## 70 2 0
## 71 7 2
## 72 4 0
## 73 3 0
## 74 9 0
## 75 7 2
## 76 6 0
## 77 4 0
## 78 7 1
## 79 5 1
## 80 9 3
## 81 5 0
## 82 7 2
## 83 5 2
## 84 5 0
## 85 7 0
## 86 6 0
## 87 4 1
## 88 4 1
## 89 7 1
## 90 9 1
## 91 6 1
## 92 6 1
## 93 9 2
## 94 6 0
## 95 3 2
## 96 10 2
## 97 5 2
## 98 7 0
## 99 4 2
## 100 5 0
## 101 15 2
## 102 5 0
## 103 8 0
## 104 9 3
## 105 7 1
## 106 2 2
## 107 3 1
## 108 5 1
## 109 4 1
## 110 6 2
## 111 2 1
## 112 5 2
## 113 3 1
## 114 9 1
## 115 6 3
## 116 3 2
## 117 6 2
## 118 6 1
## 119 8 2
## 120 5 2
## 121 6 1
## 122 7 1
## 123 8 1
## 124 9 0
## 125 11 1
## 126 4 2
## 127 2 3
## 128 2 1
## 129 6 0
## 130 5 0
## 131 5 2
## 132 4 2
## 133 7 1
## 134 7 1
## 135 4 2
## 136 6 2
## 137 6 0
## 138 4 2
## 139 13 2
## 140 5 0
## 141 5 2
## 142 3 2
## 143 4 2
## 144 4 2
## 145 4 0
## 146 5 1
## 147 4 3
## 148 6 1
## 149 3 0
## 150 8 1
## 151 2 0
## 152 3 5
## 153 1 0
## 154 3 4
## 155 4 0
## 156 6 3
## 157 3 0
## 158 3 5
## 159 6 2
## 160 2 1
## 161 6 1
## 162 2 0
## 163 8 1
## 164 2 1
## 165 1 5
## 166 5 0
## 167 3 1
## 168 7 2
## 169 6 0
## 170 5 3
## 171 5 1
## 172 5 2
## 173 7 0
## 174 4 0
## 175 5 1
## 176 7 0
## 177 5 0
## 178 4 2
## 179 6 2
## 180 3 3
## 181 2 1
## 182 1 1
## 183 1 0
## 184 4 2
## 185 8 2
## 186 1 1
## 187 4 1
## 188 5 1
## 189 4 0
## 190 4 1
## 191 4 0
## 192 2 2
## 193 3 0
## 194 3 2
## 195 3 3
## 196 3 2
## 197 2 0
## 198 4 0
## 199 3 1
## 200 1 1
## 201 4 1
## 202 4 1
## 203 1 2
## 204 5 0
## 205 2 0
## 206 4 0
## 207 2 2
## 208 7 1
## 209 0 2
## 210 3 1
## 211 4 0
## 212 2 0
## 213 5 0
## 214 2 1
## 215 1 0
## 216 3 1
## 217 4 1
## 218 2 0
## 219 3 0
## 220 1 2
## 221 4 1
## 222 2 0
## 223 2 1
## 224 2 2
## 225 5 0
## 226 7 2
## 227 2 2
## 228 2 0
## 229 3 3
## 230 5 1
## 231 1 0
## 232 6 3
## 233 4 3
## 234 0 1
## 235 3 0
## 236 4 1
## 237 1 1
## 238 3 0
## 239 5 1
## 240 4 0
## 241 3 0
## 242 1 0
## 243 1 2
## 244 5 0
## 245 2 3
## 246 1 0
## 247 3 0
## 248 2 1
## 249 3 0
## 250 3 0
## 251 7 1
## 252 2 0
## 253 7 1
## 254 5 0
## 255 6 0
## 257 4 0
## 258 3 0
## 259 4 0
## 260 2 0
## 261 1 2
## 262 3 1
## 263 2 1
## 264 0 2
## 265 3 0
## 266 4 2
## 267 2 0
## 268 4 2
## 269 4 1
## 270 1 0
## 271 2 1
## 272 6 1
## 273 2 0
## 274 3 1
## 275 2 0
## 276 2 0
## 277 4 1
## 278 3 2
## 279 1 0
## 280 3 1
## 281 3 1
## 282 0 1
## 283 4 1
## 284 3 0
## 285 4 1
## 286 3 0
## 287 1 0
## 288 2 0
## 289 1 0
## 290 3 0
## 291 3 0
## 293 2 0
## 294 1 0
## 295 2 0
## 296 0 2
## 297 7 0
## 298 2 1
## 299 1 3
## 300 1 2
## 301 2 0
## 302 1 0
## 303 2 1
## 304 3 0
## 305 2 1
## 306 1 0
## 307 1 0
## 308 3 1
## 309 4 0
## 310 2 0
## 311 3 0
## 312 1 0
## 313 2 1
## 314 3 0
## 316 2 0
## 317 1 1
## 319 2 0
## 320 1 1
## 321 0 1
## 322 1 0
## 323 1 2
## 324 1 1
## 325 2 1
## 326 2 0
## 327 3 1
## 329 2 0
## 331 0 3
## 332 3 1
## 333 1 0
## 334 0 1
## 335 3 0
## 336 1 0
## 337 1 0
## 339 3 0
## 341 2 0
## 342 5 3
## 343 2 1
## 344 0 2
## 345 5 1
## 346 2 0
## 347 1 1
## 348 1 1
## 349 2 0
## 350 2 3
## 351 1 1
## 352 2 0
## 353 3 1
## 354 1 1
## 355 3 1
## 356 1 0
## 357 2 0
## 358 3 0
## 359 1 0
## 360 2 0
## 361 3 1
## 362 2 0
## 363 1 0
## 364 0 2
## 365 1 0
## 366 1 0
## 367 0 1
## 369 0 1
## 370 1 0
## 371 2 0
## 375 3 0
## 376 2 0
## 377 1 1
## 378 0 2
## 379 1 0
## 381 2 0
## 382 0 1
## 383 1 0
## 384 1 0
## 385 1 0
## 386 2 0
## 387 0 1
## 388 3 1
## 389 2 1
## 390 1 0
## 391 1 0
## 392 0 1
## 393 2 0
## 394 0 1
## 396 0 1
## 397 1 1
## 398 1 0
## 399 3 0
## 401 4 0
## 402 1 1
## 403 1 0
## 404 1 0
## 405 1 0
## 406 0 1
## 409 1 0
## 410 1 0
## 411 1 1
## 412 2 1
## 413 1 0
## 415 3 1
## 417 3 0
## 418 2 0
## 420 2 0
## 422 1 0
## 424 2 0
## 425 2 0
## 426 1 1
## 427 4 0
## 429 2 0
## 431 1 0
## 432 2 0
## 433 2 0
## 434 1 0
## 435 2 0
## 436 1 0
## 437 3 0
## 439 3 1
## 441 2 0
## 442 1 1
## 443 1 1
## 444 2 0
## 445 3 0
## 446 0 1
## 448 0 1
## 449 2 0
## 450 2 1
## 453 0 1
## 455 1 0
## 459 1 0
## 461 2 1
## 462 3 0
## 463 1 0
## 464 2 0
## 465 1 1
## 466 1 1
## 469 1 0
## 470 1 0
## 471 1 0
## 473 2 0
## 474 1 0
## 475 0 3
## 476 1 0
## 477 1 0
## 478 1 0
## 479 4 1
## 483 1 0
## 484 1 0
## 485 1 1
## 487 2 0
## 490 1 0
## 493 2 0
## 494 3 0
## 495 2 2
## 496 1 1
## 498 1 1
## 499 0 1
## 502 2 0
## 503 0 1
## 504 1 0
## 505 0 1
## 506 1 1
## 508 2 0
## 509 1 0
## 510 1 0
## 514 1 0
## 515 0 2
## 517 1 1
## 518 2 0
## 519 2 0
## 520 1 0
## 521 1 0
## 523 0 1
## 525 1 0
## 527 0 1
## 528 3 1
## 532 1 0
## 535 0 1
## 536 1 0
## 537 2 0
## 540 1 0
## 542 1 0
## 543 1 0
## 548 0 1
## 550 0 1
## 551 1 0
## 553 1 0
## 555 1 0
## 558 1 0
## 559 1 0
## 562 1 0
## 563 4 0
## 565 1 0
## 567 2 0
## 569 1 0
## 570 1 0
## 575 0 1
## 576 1 0
## 577 1 0
## 578 0 1
## 579 1 0
## 581 1 0
## 582 1 0
## 583 1 2
## 584 1 0
## 590 2 0
## 592 0 1
## 594 1 0
## 598 1 0
## 601 1 0
## 604 1 0
## 605 2 0
## 606 1 0
## 608 1 0
## 609 1 0
## 610 1 0
## 611 1 0
## 615 1 0
## 617 2 0
## 618 1 0
## 620 2 0
## 622 1 0
## 623 1 0
## 625 1 0
## 627 1 0
## 630 0 1
## 631 0 1
## 635 0 1
## 636 0 1
## 640 1 0
## 645 1 0
## 647 1 0
## 648 0 1
## 651 1 0
## 653 1 0
## 654 0 1
## 656 0 1
## 657 1 0
## 660 1 0
## 663 1 0
## 667 0 1
## 668 0 1
## 670 1 0
## 674 1 0
## 675 1 0
## 676 0 1
## 681 1 0
## 684 1 0
## 686 1 1
## 689 1 0
## 690 1 0
## 692 1 0
## 693 2 0
## 696 0 1
## 697 1 0
## 699 0 1
## 700 1 1
## 701 1 1
## 706 1 1
## 707 0 1
## 708 1 0
## 712 0 1
## 721 0 1
## 725 1 0
## 728 1 0
## 730 1 0
## 736 1 0
## 737 0 1
## 739 0 1
## 740 0 1
## 743 1 1
## 744 0 1
## 748 2 0
## 751 0 1
## 754 1 0
## 764 2 0
## 765 1 0
## 772 1 0
## 776 1 0
## 786 1 0
## 787 1 0
## 796 0 1
## 810 0 1
## 817 1 0
## 820 1 0
## 827 1 0
## 829 1 0
## 835 0 1
## 836 1 0
## 837 1 0
## 838 0 1
## 844 1 0
## 850 0 1
## 855 1 0
## 860 0 1
## 867 1 0
## 871 1 0
## 895 1 1
## 901 0 1
## 902 1 0
## 903 0 2
## 912 0 1
## 916 2 0
## 917 0 1
## 939 0 1
## 942 1 0
## 945 1 0
## 951 1 0
## 952 0 1
## 953 0 1
## 957 1 0
## 985 1 0
## 1006 0 1
## 1012 1 0
## 1017 0 1
## 1018 1 0
## 1019 0 1
## 1022 0 1
## 1032 0 1
## 1034 0 1
## 1036 0 1
## 1038 0 1
## 1042 0 1
## 1056 1 0
## 1058 1 0
## 1063 1 2
## 1073 0 1
## 1074 1 0
## 1081 0 1
## 1090 1 0
## 1091 1 1
## 1096 1 0
## 1101 0 1
## 1108 1 0
## 1118 1 0
## 1126 1 0
## 1130 0 1
## 1134 0 1
## 1138 0 2
## 1156 1 0
## 1164 0 1
## 1174 0 1
## 1176 0 1
## 1183 0 1
## 1187 1 0
## 1190 0 1
## 1196 0 1
## 1201 1 0
## 1203 0 1
## 1209 0 1
## 1217 0 1
## 1232 0 1
## 1307 1 0
## 1353 0 1
## 1365 0 1
## 1366 1 1
## 1372 1 0
## 1447 0 1
## 1463 0 1
## 1541 0 1
## 1579 0 1
## 1594 0 1
## 1658 0 1
## 1661 0 1
## 1665 0 1
## 1691 0 1
## 1823 1 0
## 1837 1 0
## 1859 1 0
## 1916 0 1
## 1960 0 1
## 2129 1 0
## 2330 0 1
## 2870 1 0
## 3076 0 1chisq.test(gt8)## Warning in chisq.test(gt8): Chi-squared approximation may be incorrect##
## Pearson's Chi-squared test
##
## data: gt8
## X-squared = 868.97, df = 664, p-value = 1.303e-07Ta có p_value = 1.303e-07 < 0.05 nên ta bác bỏ giả thuyết H0. Nghĩa là, Thời lượng cuộc gọi (duration) và quyết định đăng kí mở tài khoản (term_deposit) liên quan với nhau
2.0.9 Số lần liên hệ trước đó (previous) và quyết định đăng kí mở tài khoản (term_deposit)
Giả thuyết:
H0: Số lần liên hệ trước đó (previous) và quyết định đăng kí mở tài khoản (term_deposit) độc lập với nhau
H1: Số lần liên hệ trước đó (previous) và quyết định đăng kí mở tài khoản (term_deposit) không độc lập với nhau
gt9 <- table(bank$previous, bank$term_deposit)
gt9##
## 0 1
## 1 673 196
## 2 438 117
## 3 179 50
## 4 96 26
## 5 67 13
## 6 45 4
## 7 31 3
## 8 19 2
## 9 8 1
## 10 7 2
## 11 5 1
## 12 7 0
## 13 1 1
## 14 2 0
## 15 1 0
## 18 1 0
## 19 1 0
## 20 0 1
## 21 1 1chisq.test(gt9)## Warning in chisq.test(gt9): Chi-squared approximation may be incorrect##
## Pearson's Chi-squared test
##
## data: gt9
## X-squared = 21.682, df = 18, p-value = 0.2464Ta có p_value = 0.2464 > 0.05 nên ta chưa đủ cơ sở bác bỏ giả thuyết H0. Nghĩa là, Số lần liên hệ trước đó (previous) và quyết định đăng kí mở tài khoản (term_deposit) độc lập với nhau
3 BTVN TUẦN 3-4: Thống kê mô tả và Thống kê suy diễn
Đối với đề tài nghiên cứu về chiến dịch tiếp thị trực tiếp (telesale) của một ngân hàng nhằm tìm kiếm khách hàng tiềm năng về tiền gửi có kỳ hạn. Bộ dữ liệu gồm 2000 quan sát với 10 biến (6 biến định tính và 4 biến định lượng)
3.1 Thống kê mô tả các biến định tính
setwd("D:/HN")
bank <- read.csv("databank.csv", header=TRUE)
str(bank)## 'data.frame': 2000 obs. of 11 variables:
## $ ID : int 1 2 3 4 5 6 7 8 9 10 ...
## $ age : int 50 41 36 31 51 27 27 59 43 46 ...
## $ job : chr "management" "technician" "entrepreneur" "blue-collar" ...
## $ marital : int 1 2 1 0 0 2 1 0 1 2 ...
## $ education : chr "secondary" "secondary" "secondary" "tertiary" ...
## $ default : int 0 0 0 0 0 0 0 0 0 0 ...
## $ balance : int -111 -329 904 106 300 245 494 1774 1063 -191 ...
## $ housing : int 1 0 0 1 0 1 0 0 1 1 ...
## $ duration : int 19 13 36 67 8 7 16 14 141 674 ...
## $ previous : int 11 8 9 2 6 7 10 9 3 3 ...
## $ term_deposit: int 0 0 0 0 0 0 0 0 0 0 ...bank2 <- bank[,c("age","job","marital", "education","default", "housing", "term_deposit")]3.1.0.1 Biến độ tuổi (age)
bank2 |> ggplot(aes(bank$age)) + geom_bar() + ylab ("Số khách hàng") + xlab ("Độ tuổi")
Trong số các khách hàng được khảo sát, ta có thể thấy độ tuổi từ 20-40 tuổi chiếm tỉ trọng lớn nhất.
3.1.0.2 Biến công việc (job)
bank2 |> ggplot(aes(bank$job)) + geom_bar() + ylab ("Số khách hàng") + xlab ("Công việc")
prop.table(table(bank$job))##
## admin. blue-collar entrepreneur housemaid management
## 0.1260 0.3375 0.0280 0.0105 0.1390
## retired self-employed services student technician
## 0.0310 0.0240 0.1205 0.0135 0.1430
## unemployed unknown
## 0.0240 0.0030Trong số 2000 khách hàng, công nhân và kĩ thuật viên là 2 ngành nghề chiếm tỉ trọng cao nhất với 33.75% và 14.3%
3.1.0.3 Biến tình trạng hôn nhân (marital)
bank2 |> ggplot(aes(bank$marital)) + geom_bar() + ylab ("Số khách hàng") + xlab ("Tình trạng hôn nhân")
prop.table(table(bank$marital))##
## 0 1 2
## 0.1075 0.3465 0.5460Trong số 2000 khách hàng, tình trạng độc thân chiếm tỉ trọng cao nhất với 54.6%, kế đó là tình trạng đã kết hôn với 34.65% và cuối cùng là đã ly hôn với 10.75%
3.1.0.4 Biến trình độ học vấn (education)
bank2 |> ggplot(aes(bank$education)) + geom_bar() + ylab ("Số khách hàng") + xlab ("Trình độ học vấn")
prop.table(table(bank$education))##
## primary secondary tertiary unknown
## 0.1265 0.5135 0.3200 0.0400Đối với trình độ học vấn của khách hàng, khách hàng có trình độ cao học và trung học phổ thông chiếm tỷ lệ nhiều nhất. Trình độ cao đẳng chiếm 32% và trung học phổ thông chiếm 51.35%.
3.1.0.5 Biến tín dụng (default)
bank2 |> ggplot(aes(bank$default)) + geom_bar() + ylab ("Số khách hàng") + xlab ("Tình trạng tín dụng")
prop.table(table(bank$default))##
## 0 1
## 0.993 0.007Tình trạng khách hàng đã có tín dụng hay chưa được thống kê như sau: số khách hàng đã có chiếm 99.3% và chưa có chỉ chiếm 0.07%.
3.1.0.6 Biến nhà ở (housing)
bank2 |> ggplot(aes(bank$housing)) + geom_bar() + ylab ("Số khách hàng") + xlab ("Tình trạng nhà ở")
prop.table(table(bank$housing))##
## 0 1
## 0.443 0.557Tình trạng khách hàng đã có nhà hay chưa được thống kê như sau: số khách hàng đã có nhà chiếm 44.3% và chưa có nhà chiếm 55.7%.
3.1.0.7 Biến tình trạng đăng kí tài khoản (term_deposit)
bank2 |> ggplot(aes(bank$housing)) + geom_bar() + ylab ("Số khách hàng") + xlab ("Tình trạng đăng kí tài khoản")
prop.table(table(bank$term_deposit))##
## 0 1
## 0.791 0.209Thống kê khách hàng có đăng kí tài khoản tiền gửi kỳ hạn hay không như sau: số khách hàng phản hồi đăng kí chiếm 79.1% và không đăng kí chiếm 20.9%.
3.2 Thống kê mô tả các biến định lượng
3.2.1 Biến số dư tài khoản (balance)
bank3 <- data.frame(bank$balance)
summary(bank3)## bank.balance
## Min. :-2712.0
## 1st Qu.: 205.8
## Median : 665.0
## Mean : 1549.5
## 3rd Qu.: 1726.0
## Max. :32685.0prop.table(table(bank$balance))##
## -2712 -1455 -932 -898 -812 -675 -670 -665 -613 -550 -547
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## -538 -522 -521 -491 -464 -462 -456 -435 -421 -417 -398
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## -393 -382 -378 -376 -359 -329 -321 -318 -312 -292 -277
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005
## -254 -253 -251 -220 -212 -210 -197 -194 -191 -187 -158
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## -152 -151 -149 -145 -130 -125 -121 -117 -111 -101 -100
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## -97 -93 -91 -85 -84 -73 -68 -61 -60 -57 -56
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## -55 -54 -53 -43 -41 -39 -34 -30 -28 -19 -17
## 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## -5 -3 -2 -1 0 1 2 3 4 5 6
## 0.0005 0.0005 0.0005 0.0010 0.0610 0.0030 0.0020 0.0020 0.0015 0.0025 0.0010
## 8 9 10 11 12 13 15 16 18 19 20
## 0.0005 0.0005 0.0010 0.0020 0.0005 0.0005 0.0005 0.0015 0.0010 0.0005 0.0010
## 21 23 24 25 26 27 28 29 31 32 33
## 0.0025 0.0015 0.0005 0.0020 0.0020 0.0005 0.0005 0.0005 0.0015 0.0005 0.0015
## 34 35 36 37 39 40 42 43 45 46 47
## 0.0005 0.0010 0.0005 0.0005 0.0005 0.0010 0.0015 0.0010 0.0005 0.0015 0.0005
## 48 49 51 52 53 54 56 57 58 59 60
## 0.0010 0.0005 0.0005 0.0015 0.0010 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005
## 61 63 66 67 68 70 71 73 74 76 78
## 0.0005 0.0010 0.0010 0.0005 0.0015 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 79 80 81 82 84 86 87 88 89 91 92
## 0.0010 0.0005 0.0015 0.0010 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 93 94 95 96 99 101 102 103 105 106 107
## 0.0010 0.0005 0.0005 0.0015 0.0010 0.0015 0.0005 0.0010 0.0015 0.0020 0.0005
## 109 110 111 113 114 115 116 117 119 120 121
## 0.0005 0.0010 0.0025 0.0010 0.0005 0.0010 0.0005 0.0005 0.0005 0.0010 0.0010
## 122 123 124 126 127 128 129 130 131 132 133
## 0.0015 0.0010 0.0005 0.0020 0.0020 0.0005 0.0005 0.0005 0.0005 0.0020 0.0010
## 134 135 136 137 138 139 140 144 145 146 148
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0015 0.0005 0.0005 0.0005 0.0010 0.0005
## 150 152 153 154 155 157 158 159 160 161 163
## 0.0015 0.0005 0.0005 0.0010 0.0010 0.0005 0.0025 0.0015 0.0005 0.0005 0.0005
## 164 165 167 169 171 172 174 176 177 178 180
## 0.0010 0.0005 0.0015 0.0005 0.0005 0.0010 0.0005 0.0010 0.0005 0.0005 0.0020
## 182 183 184 185 186 187 188 189 190 191 193
## 0.0010 0.0015 0.0020 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005
## 194 195 196 197 198 200 201 202 203 204 205
## 0.0005 0.0010 0.0010 0.0005 0.0010 0.0005 0.0020 0.0010 0.0005 0.0005 0.0015
## 206 207 209 211 212 213 214 215 217 218 223
## 0.0010 0.0005 0.0010 0.0010 0.0010 0.0005 0.0005 0.0020 0.0020 0.0005 0.0010
## 227 228 229 233 234 237 238 240 241 242 243
## 0.0005 0.0005 0.0005 0.0010 0.0005 0.0010 0.0020 0.0005 0.0005 0.0015 0.0005
## 244 245 247 248 250 252 254 255 256 258 259
## 0.0005 0.0005 0.0010 0.0010 0.0025 0.0005 0.0010 0.0010 0.0005 0.0010 0.0010
## 260 261 264 265 266 267 268 269 270 271 272
## 0.0005 0.0005 0.0015 0.0005 0.0005 0.0010 0.0010 0.0005 0.0015 0.0015 0.0005
## 273 274 275 277 278 280 281 283 285 287 288
## 0.0005 0.0010 0.0015 0.0005 0.0005 0.0005 0.0015 0.0005 0.0020 0.0010 0.0005
## 289 290 292 293 294 296 297 298 299 300 302
## 0.0005 0.0005 0.0010 0.0015 0.0005 0.0005 0.0010 0.0005 0.0005 0.0020 0.0010
## 303 304 306 309 310 311 312 313 314 315 316
## 0.0005 0.0005 0.0005 0.0020 0.0010 0.0005 0.0015 0.0010 0.0010 0.0025 0.0010
## 317 318 319 320 321 322 325 326 327 330 331
## 0.0010 0.0015 0.0005 0.0005 0.0010 0.0010 0.0010 0.0005 0.0010 0.0005 0.0005
## 332 333 334 335 336 337 342 344 345 346 347
## 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0010 0.0010 0.0005
## 348 349 350 351 352 354 355 356 357 358 359
## 0.0005 0.0010 0.0005 0.0015 0.0010 0.0005 0.0005 0.0015 0.0010 0.0005 0.0005
## 360 361 362 363 367 369 370 371 373 375 376
## 0.0005 0.0005 0.0005 0.0010 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 377 380 381 382 383 385 387 388 390 392 393
## 0.0015 0.0005 0.0020 0.0010 0.0010 0.0005 0.0025 0.0015 0.0005 0.0005 0.0015
## 395 396 397 398 399 401 403 404 405 406 407
## 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0015 0.0010 0.0010 0.0010 0.0005
## 408 409 410 413 414 416 417 419 420 421 423
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0015 0.0005 0.0005 0.0005 0.0015
## 424 426 428 429 430 431 432 433 436 438 439
## 0.0010 0.0005 0.0005 0.0005 0.0020 0.0005 0.0005 0.0005 0.0005 0.0015 0.0010
## 440 442 443 444 445 446 447 448 449 452 453
## 0.0015 0.0010 0.0010 0.0005 0.0015 0.0015 0.0005 0.0010 0.0005 0.0005 0.0005
## 457 458 459 462 464 467 470 471 473 474 475
## 0.0010 0.0005 0.0015 0.0010 0.0005 0.0010 0.0005 0.0005 0.0010 0.0005 0.0005
## 476 477 479 480 483 484 485 486 488 489 490
## 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0015 0.0010 0.0005
## 491 492 493 494 496 497 499 500 501 503 504
## 0.0010 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0010 0.0005 0.0015 0.0005
## 505 506 507 508 510 511 513 515 516 517 518
## 0.0005 0.0010 0.0010 0.0005 0.0010 0.0010 0.0005 0.0005 0.0010 0.0010 0.0005
## 519 522 523 524 525 528 529 530 531 533 536
## 0.0010 0.0015 0.0030 0.0010 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 539 540 541 542 543 544 545 546 549 554 555
## 0.0005 0.0005 0.0005 0.0005 0.0015 0.0005 0.0010 0.0010 0.0010 0.0015 0.0005
## 556 558 559 560 561 562 565 566 569 571 572
## 0.0005 0.0010 0.0010 0.0010 0.0010 0.0010 0.0010 0.0005 0.0005 0.0005 0.0005
## 574 575 576 577 581 582 586 587 588 589 593
## 0.0015 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0015 0.0005 0.0005 0.0005
## 596 598 600 601 602 606 607 609 611 612 614
## 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005
## 616 617 618 620 623 624 625 626 627 629 631
## 0.0005 0.0005 0.0005 0.0010 0.0005 0.0010 0.0005 0.0005 0.0010 0.0005 0.0010
## 632 635 638 640 642 643 644 646 647 648 649
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0010 0.0005 0.0010
## 651 653 654 655 657 658 659 660 661 663 664
## 0.0005 0.0005 0.0005 0.0015 0.0010 0.0010 0.0005 0.0005 0.0005 0.0010 0.0005
## 665 666 669 671 672 673 674 676 677 678 681
## 0.0015 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0010 0.0005 0.0010
## 682 683 685 686 687 688 689 690 691 692 694
## 0.0010 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0010
## 695 696 697 698 700 702 703 705 706 708 712
## 0.0010 0.0005 0.0005 0.0005 0.0010 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005
## 713 714 715 718 719 720 722 725 726 728 729
## 0.0005 0.0010 0.0010 0.0005 0.0005 0.0010 0.0010 0.0010 0.0010 0.0010 0.0005
## 730 731 732 735 736 738 739 741 744 745 749
## 0.0005 0.0010 0.0005 0.0005 0.0010 0.0005 0.0005 0.0010 0.0010 0.0005 0.0010
## 750 751 753 754 755 757 758 759 760 764 765
## 0.0005 0.0005 0.0015 0.0005 0.0005 0.0010 0.0005 0.0005 0.0010 0.0005 0.0005
## 766 767 770 771 778 779 781 782 783 784 790
## 0.0010 0.0010 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005
## 791 794 795 796 799 800 802 803 805 807 810
## 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010
## 811 816 817 818 821 823 824 825 827 829 831
## 0.0010 0.0005 0.0010 0.0005 0.0005 0.0010 0.0010 0.0005 0.0005 0.0005 0.0005
## 834 837 840 841 844 852 853 854 855 858 859
## 0.0005 0.0015 0.0005 0.0005 0.0010 0.0005 0.0005 0.0010 0.0010 0.0005 0.0005
## 861 862 863 867 868 870 871 873 875 876 877
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 879 881 882 883 887 890 893 894 897 898 899
## 0.0010 0.0005 0.0005 0.0010 0.0010 0.0010 0.0005 0.0005 0.0015 0.0005 0.0005
## 900 902 903 904 906 909 915 917 922 923 924
## 0.0010 0.0010 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 925 926 934 935 937 938 939 941 946 947 948
## 0.0010 0.0010 0.0005 0.0010 0.0015 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 951 952 953 956 958 959 963 964 968 970 974
## 0.0010 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005
## 978 979 982 983 984 985 987 988 990 991 992
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0015 0.0005 0.0005 0.0005 0.0005 0.0005
## 994 995 997 999 1000 1004 1009 1012 1016 1018 1019
## 0.0005 0.0010 0.0005 0.0005 0.0005 0.0020 0.0005 0.0010 0.0005 0.0005 0.0005
## 1021 1022 1029 1030 1035 1036 1045 1047 1048 1055 1057
## 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005
## 1058 1062 1063 1064 1066 1068 1070 1072 1074 1076 1078
## 0.0005 0.0010 0.0015 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 1084 1085 1088 1090 1094 1096 1097 1099 1101 1107 1111
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0010 0.0005 0.0005
## 1114 1116 1123 1129 1130 1131 1134 1135 1136 1138 1139
## 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0010 0.0005 0.0005 0.0010 0.0005
## 1143 1144 1145 1147 1150 1154 1158 1159 1160 1161 1162
## 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 1174 1175 1177 1180 1184 1187 1191 1198 1204 1205 1207
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0010 0.0005 0.0005 0.0005
## 1209 1222 1228 1231 1232 1234 1235 1236 1242 1245 1250
## 0.0005 0.0005 0.0005 0.0005 0.0010 0.0010 0.0005 0.0010 0.0005 0.0005 0.0010
## 1254 1256 1257 1259 1261 1263 1265 1268 1271 1273 1274
## 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 1275 1277 1280 1281 1282 1283 1285 1287 1290 1292 1293
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0015 0.0005 0.0010 0.0010
## 1296 1297 1300 1301 1306 1311 1314 1315 1316 1318 1319
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005
## 1323 1327 1332 1335 1341 1342 1344 1347 1350 1352 1354
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0010 0.0010 0.0005 0.0005
## 1358 1363 1364 1367 1375 1376 1377 1381 1384 1387 1389
## 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010
## 1393 1397 1405 1406 1409 1411 1412 1414 1418 1420 1428
## 0.0005 0.0010 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 1443 1450 1451 1457 1468 1470 1473 1474 1480 1493 1499
## 0.0010 0.0010 0.0010 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005
## 1506 1512 1515 1518 1521 1528 1534 1539 1543 1544 1548
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005
## 1550 1554 1557 1562 1565 1576 1586 1588 1590 1592 1595
## 0.0005 0.0010 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010
## 1597 1598 1599 1601 1610 1612 1613 1617 1624 1631 1636
## 0.0005 0.0010 0.0005 0.0005 0.0005 0.0010 0.0010 0.0010 0.0005 0.0005 0.0015
## 1641 1646 1674 1681 1683 1684 1693 1698 1702 1704 1714
## 0.0010 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 1716 1723 1725 1729 1730 1738 1740 1743 1746 1756 1758
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0010 0.0005 0.0005 0.0005
## 1759 1762 1765 1770 1772 1773 1774 1775 1778 1781 1790
## 0.0005 0.0010 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010
## 1801 1803 1804 1807 1808 1815 1819 1820 1822 1831 1832
## 0.0010 0.0005 0.0005 0.0010 0.0005 0.0010 0.0010 0.0005 0.0005 0.0005 0.0010
## 1836 1840 1846 1847 1859 1861 1872 1877 1885 1908 1912
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 1918 1924 1925 1927 1928 1933 1943 1944 1951 1957 1972
## 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010
## 1981 1988 1993 1997 2000 2010 2012 2021 2030 2033 2037
## 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005
## 2038 2047 2061 2063 2068 2070 2080 2084 2088 2110 2121
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 2126 2133 2135 2137 2139 2140 2143 2149 2152 2171 2173
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010
## 2174 2183 2185 2189 2203 2232 2235 2245 2249 2265 2266
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005
## 2273 2281 2284 2290 2294 2301 2308 2310 2317 2320 2321
## 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 2326 2332 2337 2340 2346 2351 2353 2354 2361 2374 2384
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 2397 2403 2408 2416 2422 2424 2441 2442 2454 2466 2484
## 0.0005 0.0005 0.0005 0.0010 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 2489 2503 2506 2509 2511 2519 2523 2530 2531 2539 2544
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010
## 2549 2553 2554 2556 2557 2580 2581 2583 2590 2591 2603
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 2613 2614 2616 2628 2643 2644 2646 2647 2648 2651 2656
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 2658 2660 2663 2667 2669 2681 2687 2689 2693 2707 2709
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005
## 2722 2726 2729 2730 2731 2732 2734 2735 2740 2745 2756
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 2765 2772 2774 2780 2786 2820 2823 2833 2847 2848 2849
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 2850 2855 2869 2881 2887 2892 2895 2901 2904 2909 2923
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 2926 2953 2960 2964 2976 2981 2987 2993 3000 3049 3092
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005
## 3102 3103 3123 3132 3136 3161 3164 3168 3170 3186 3187
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 3234 3247 3268 3270 3274 3286 3301 3302 3315 3323 3342
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005
## 3349 3358 3404 3407 3415 3427 3434 3462 3469 3473 3480
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005
## 3498 3508 3512 3529 3552 3568 3576 3588 3611 3612 3623
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 3640 3648 3649 3658 3663 3665 3676 3687 3690 3698 3713
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 3729 3730 3733 3735 3738 3740 3751 3754 3771 3773 3777
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 3820 3858 3915 3917 3931 3943 3948 3953 3981 4020 4047
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 4066 4099 4101 4105 4112 4126 4198 4269 4279 4319 4348
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 4365 4367 4394 4415 4447 4459 4461 4562 4564 4581 4588
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 4596 4613 4629 4657 4659 4661 4700 4726 4736 4787 4788
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005
## 4808 4873 4886 4910 4923 4979 4987 4990 4991 5005 5012
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 5041 5043 5060 5076 5087 5115 5131 5157 5250 5251 5253
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 5271 5355 5359 5367 5396 5399 5417 5445 5467 5521 5542
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 5553 5561 5563 5608 5679 5689 5698 5737 5763 5780 5798
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 5810 5916 5943 5949 5969 6101 6106 6158 6251 6384 6422
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005
## 6468 6483 6495 6533 6551 6651 6662 6684 6695 6706 6836
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 6994 7179 7263 7336 7357 7387 7433 7613 7685 7702 7962
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 8089 8104 8112 8180 8195 8238 8262 8304 8311 8345 8381
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 8623 8627 8666 8674 8749 8860 8866 8929 9324 9329 9601
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 9610 9676 10005 10045 10152 10180 10185 10200 10469 10600 10768
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 11066 11174 11385 11387 11555 11767 11862 11891 12039 12048 12114
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 12159 12857 12926 13408 13654 13669 13849 13874 14344 14850 15261
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 15459 15485 16649 17441 17609 19102 20727 20806 21446 23663 23878
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 26306 26721 26831 32685
## 0.0005 0.0005 0.0005 0.00053.2.2 Biến thời lượng cuộc gọi (duration)
bank4 <- data.frame(bank$duration)
summary(bank4)## bank.duration
## Min. : 1.0
## 1st Qu.: 104.0
## Median : 185.0
## Mean : 272.1
## 3rd Qu.: 337.5
## Max. :3076.0prop.table(table(bank$duration))##
## 1 2 7 8 9 10 11 12 13 14 15
## 0.0005 0.0005 0.0020 0.0025 0.0010 0.0005 0.0020 0.0035 0.0040 0.0015 0.0045
## 16 17 18 19 20 21 22 23 24 25 26
## 0.0020 0.0025 0.0020 0.0010 0.0005 0.0005 0.0010 0.0010 0.0010 0.0015 0.0010
## 27 28 29 30 32 33 34 35 36 37 38
## 0.0010 0.0005 0.0015 0.0015 0.0005 0.0015 0.0010 0.0020 0.0025 0.0020 0.0015
## 39 40 41 42 43 44 45 46 47 48 49
## 0.0025 0.0015 0.0030 0.0010 0.0030 0.0040 0.0025 0.0015 0.0030 0.0035 0.0030
## 51 52 53 54 55 56 57 58 59 60 61
## 0.0015 0.0015 0.0015 0.0015 0.0015 0.0035 0.0015 0.0055 0.0030 0.0030 0.0045
## 62 63 64 65 66 67 68 69 70 71 72
## 0.0010 0.0010 0.0015 0.0020 0.0030 0.0025 0.0015 0.0020 0.0010 0.0045 0.0020
## 73 74 75 76 77 78 79 80 81 82 83
## 0.0015 0.0045 0.0045 0.0030 0.0020 0.0040 0.0030 0.0060 0.0025 0.0045 0.0035
## 84 85 86 87 88 89 90 91 92 93 94
## 0.0025 0.0035 0.0030 0.0025 0.0025 0.0040 0.0050 0.0035 0.0035 0.0055 0.0030
## 95 96 97 98 99 100 101 102 103 104 105
## 0.0025 0.0060 0.0035 0.0035 0.0030 0.0025 0.0085 0.0025 0.0040 0.0060 0.0040
## 106 107 108 109 110 111 112 113 114 115 116
## 0.0020 0.0020 0.0030 0.0025 0.0040 0.0015 0.0035 0.0020 0.0050 0.0045 0.0025
## 117 118 119 120 121 122 123 124 125 126 127
## 0.0040 0.0035 0.0050 0.0035 0.0035 0.0040 0.0045 0.0045 0.0060 0.0030 0.0025
## 128 129 130 131 132 133 134 135 136 137 138
## 0.0015 0.0030 0.0025 0.0035 0.0030 0.0040 0.0040 0.0030 0.0040 0.0030 0.0030
## 139 140 141 142 143 144 145 146 147 148 149
## 0.0075 0.0025 0.0035 0.0025 0.0030 0.0030 0.0020 0.0030 0.0035 0.0035 0.0015
## 150 151 152 153 154 155 156 157 158 159 160
## 0.0045 0.0010 0.0040 0.0005 0.0035 0.0020 0.0045 0.0015 0.0040 0.0040 0.0015
## 161 162 163 164 165 166 167 168 169 170 171
## 0.0035 0.0010 0.0045 0.0015 0.0030 0.0025 0.0020 0.0045 0.0030 0.0040 0.0030
## 172 173 174 175 176 177 178 179 180 181 182
## 0.0035 0.0035 0.0020 0.0030 0.0035 0.0025 0.0030 0.0040 0.0030 0.0015 0.0010
## 183 184 185 186 187 188 189 190 191 192 193
## 0.0005 0.0030 0.0050 0.0010 0.0025 0.0030 0.0020 0.0025 0.0020 0.0020 0.0015
## 194 195 196 197 198 199 200 201 202 203 204
## 0.0025 0.0030 0.0025 0.0010 0.0020 0.0020 0.0010 0.0025 0.0025 0.0015 0.0025
## 205 206 207 208 209 210 211 212 213 214 215
## 0.0010 0.0020 0.0020 0.0040 0.0010 0.0020 0.0020 0.0010 0.0025 0.0015 0.0005
## 216 217 218 219 220 221 222 223 224 225 226
## 0.0020 0.0025 0.0010 0.0015 0.0015 0.0025 0.0010 0.0015 0.0020 0.0025 0.0045
## 227 228 229 230 231 232 233 234 235 236 237
## 0.0020 0.0010 0.0030 0.0030 0.0005 0.0045 0.0035 0.0005 0.0015 0.0025 0.0010
## 238 239 240 241 242 243 244 245 246 247 248
## 0.0015 0.0030 0.0020 0.0015 0.0005 0.0015 0.0025 0.0025 0.0005 0.0015 0.0015
## 249 250 251 252 253 254 255 257 258 259 260
## 0.0015 0.0015 0.0040 0.0010 0.0040 0.0025 0.0030 0.0020 0.0015 0.0020 0.0010
## 261 262 263 264 265 266 267 268 269 270 271
## 0.0015 0.0020 0.0015 0.0010 0.0015 0.0030 0.0010 0.0030 0.0025 0.0005 0.0015
## 272 273 274 275 276 277 278 279 280 281 282
## 0.0035 0.0010 0.0020 0.0010 0.0010 0.0025 0.0025 0.0005 0.0020 0.0020 0.0005
## 283 284 285 286 287 288 289 290 291 293 294
## 0.0025 0.0015 0.0025 0.0015 0.0005 0.0010 0.0005 0.0015 0.0015 0.0010 0.0005
## 295 296 297 298 299 300 301 302 303 304 305
## 0.0010 0.0010 0.0035 0.0015 0.0020 0.0015 0.0010 0.0005 0.0015 0.0015 0.0015
## 306 307 308 309 310 311 312 313 314 316 317
## 0.0005 0.0005 0.0020 0.0020 0.0010 0.0015 0.0005 0.0015 0.0015 0.0010 0.0010
## 319 320 321 322 323 324 325 326 327 329 331
## 0.0010 0.0010 0.0005 0.0005 0.0015 0.0010 0.0015 0.0010 0.0020 0.0010 0.0015
## 332 333 334 335 336 337 339 341 342 343 344
## 0.0020 0.0005 0.0005 0.0015 0.0005 0.0005 0.0015 0.0010 0.0040 0.0015 0.0010
## 345 346 347 348 349 350 351 352 353 354 355
## 0.0030 0.0010 0.0010 0.0010 0.0010 0.0025 0.0010 0.0010 0.0020 0.0010 0.0020
## 356 357 358 359 360 361 362 363 364 365 366
## 0.0005 0.0010 0.0015 0.0005 0.0010 0.0020 0.0010 0.0005 0.0010 0.0005 0.0005
## 367 369 370 371 375 376 377 378 379 381 382
## 0.0005 0.0005 0.0005 0.0010 0.0015 0.0010 0.0010 0.0010 0.0005 0.0010 0.0005
## 383 384 385 386 387 388 389 390 391 392 393
## 0.0005 0.0005 0.0005 0.0010 0.0005 0.0020 0.0015 0.0005 0.0005 0.0005 0.0010
## 394 396 397 398 399 401 402 403 404 405 406
## 0.0005 0.0005 0.0010 0.0005 0.0015 0.0020 0.0010 0.0005 0.0005 0.0005 0.0005
## 409 410 411 412 413 415 417 418 420 422 424
## 0.0005 0.0005 0.0010 0.0015 0.0005 0.0020 0.0015 0.0010 0.0010 0.0005 0.0010
## 425 426 427 429 431 432 433 434 435 436 437
## 0.0010 0.0010 0.0020 0.0010 0.0005 0.0010 0.0010 0.0005 0.0010 0.0005 0.0015
## 439 441 442 443 444 445 446 448 449 450 453
## 0.0020 0.0010 0.0010 0.0010 0.0010 0.0015 0.0005 0.0005 0.0010 0.0015 0.0005
## 455 459 461 462 463 464 465 466 469 470 471
## 0.0005 0.0005 0.0015 0.0015 0.0005 0.0010 0.0010 0.0010 0.0005 0.0005 0.0005
## 473 474 475 476 477 478 479 483 484 485 487
## 0.0010 0.0005 0.0015 0.0005 0.0005 0.0005 0.0025 0.0005 0.0005 0.0010 0.0010
## 490 493 494 495 496 498 499 502 503 504 505
## 0.0005 0.0010 0.0015 0.0020 0.0010 0.0010 0.0005 0.0010 0.0005 0.0005 0.0005
## 506 508 509 510 514 515 517 518 519 520 521
## 0.0010 0.0010 0.0005 0.0005 0.0005 0.0010 0.0010 0.0010 0.0010 0.0005 0.0005
## 523 525 527 528 532 535 536 537 540 542 543
## 0.0005 0.0005 0.0005 0.0020 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005
## 548 550 551 553 555 558 559 562 563 565 567
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0020 0.0005 0.0010
## 569 570 575 576 577 578 579 581 582 583 584
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0015 0.0005
## 590 592 594 598 601 604 605 606 608 609 610
## 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005
## 611 615 617 618 620 622 623 625 627 630 631
## 0.0005 0.0005 0.0010 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 635 636 640 645 647 648 651 653 654 656 657
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 660 663 667 668 670 674 675 676 681 684 686
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010
## 689 690 692 693 696 697 699 700 701 706 707
## 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0010 0.0010 0.0010 0.0005
## 708 712 721 725 728 730 736 737 739 740 743
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010
## 744 748 751 754 764 765 772 776 786 787 796
## 0.0005 0.0010 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 810 817 820 827 829 835 836 837 838 844 850
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 855 860 867 871 895 901 902 903 912 916 917
## 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0010 0.0005 0.0010 0.0005
## 939 942 945 951 952 953 957 985 1006 1012 1017
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 1018 1019 1022 1032 1034 1036 1038 1042 1056 1058 1063
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0015
## 1073 1074 1081 1090 1091 1096 1101 1108 1118 1126 1130
## 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 1134 1138 1156 1164 1174 1176 1183 1187 1190 1196 1201
## 0.0005 0.0010 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 1203 1209 1217 1232 1307 1353 1365 1366 1372 1447 1463
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0010 0.0005 0.0005 0.0005
## 1541 1579 1594 1658 1661 1665 1691 1823 1837 1859 1916
## 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005 0.0005
## 1960 2129 2330 2870 3076
## 0.0005 0.0005 0.0005 0.0005 0.00053.2.3 Biến số lần liên hệ trước đó (previous)
bank5 <- data.frame(bank$previous)
summary(bank5)## bank.previous
## Min. : 1.000
## 1st Qu.: 1.000
## Median : 2.000
## Mean : 2.372
## 3rd Qu.: 3.000
## Max. :21.000prop.table(table(bank$previous))##
## 1 2 3 4 5 6 7 8 9 10 11
## 0.4345 0.2775 0.1145 0.0610 0.0400 0.0245 0.0170 0.0105 0.0045 0.0045 0.0030
## 12 13 14 15 18 19 20 21
## 0.0035 0.0010 0.0010 0.0005 0.0005 0.0005 0.0005 0.00103.3 Tính rủi ro tương đối
3.3.1 Rủi ro tương đối giữa biến công việc và quyết định đăng kí tài khoản tiền gửi kỳ hạn
rik <- table(bank$job, bank$term_deposit)
addmargins(rik)##
## 0 1 Sum
## admin. 202 50 252
## blue-collar 534 141 675
## entrepreneur 41 15 56
## housemaid 13 8 21
## management 225 53 278
## retired 50 12 62
## self-employed 41 7 48
## services 185 56 241
## student 21 6 27
## technician 232 54 286
## unemployed 35 13 48
## unknown 3 3 6
## Sum 1582 418 20003.3.2 Rủi ro tương đối giữa biến trình độ học vấn và quyết định đăng kí tài khoản tiền gửi kỳ hạn
rik1 <- table(bank$education, bank$term_deposit)
addmargins(rik1)##
## 0 1 Sum
## primary 220 33 253
## secondary 838 189 1027
## tertiary 456 184 640
## unknown 68 12 80
## Sum 1582 418 20004 BTVN TUẦN 2
Dữ liệu nghiên cứu về chiến dịch tiếp thị trực tiếp (telesale) của một ngân hàng nhằm tìm kiếm tài năng về tiền gửi có kỳ hạn. Bộ dữ liệu gồm 2000 quan sát với 10 biến (6 biến định tính và 4 biến định lượng)
Giải thích biến
age: tuổi
job: công việc
marital: tình trạng hôn nhân (0: đã ly hôn, 1: đã kết hôn, 2: độc thân)
education: học vấn
default: có tín dụng chưa? (0:có, 1: không)
balance: số dư tài khoản
housing: Đã có nhà chưa?(0: có, 1: chưa)
duration: Thời lượng cuộc gọi (giây)
previous: Số lần liên hệ trước đó
term_deposit: KH có đăng ký tài khoản tiền gửi kỳ hạn hay không (0: có, 1: không)
Biến định lượng phụ thuộc là balance (số dư tài khoản) vì biến này chịu tác động khá lớn từ tuổi tác, công việc cũng như là học vấn.
Biến định tính phụ thuộc là quyết định đăng kí tài khoản tiền gửi có kì hạn vì đề tài cần nghiên cứu về chiến dịch tiếp thị trực tiếp (telesale) của một ngân hàng nhằm tìm kiếm khách hàng tiềm năng về tiền gửi có kỳ hạn.
5 BTVN TUẦN 1
Dữ liệu nghiên cứu về chiến dịch tiếp thị trực tiếp (telesale) của một ngân hàng nhằm tìm kiếm khách hàng tiềm năng về tiền gửi có kỳ hạn. Bộ dữ liệu gồm 2000 quan sát, với 10 biến (6 biến định tính và 4 biến định lượng)
5.1 Giải thích biến:
age: tuổi
job: công việc
marital: tình trạng hôn nhân (0: Đã ly hôn, 1: Đã kết hôn, 2: Độc thân)
education: học vấn
default: có tín dụng chưa? (0: có, 1: chưa)
balance: số dư tài khoản
housing: Đã có nhà chưa? (0: có, 1: chưa)
duration: Thời lượng cuộc gọi (giây)
previous: Số lần liên hệ trước đó
term_deposit: KH có đăng ký tài khoản tiền gửi kỳ hạn hay không (0: có, 1: không)
setwd("D:/HN")
data1 <- read.csv("databank.csv", header=TRUE)
str(data1)## 'data.frame': 2000 obs. of 11 variables:
## $ ID : int 1 2 3 4 5 6 7 8 9 10 ...
## $ age : int 50 41 36 31 51 27 27 59 43 46 ...
## $ job : chr "management" "technician" "entrepreneur" "blue-collar" ...
## $ marital : int 1 2 1 0 0 2 1 0 1 2 ...
## $ education : chr "secondary" "secondary" "secondary" "tertiary" ...
## $ default : int 0 0 0 0 0 0 0 0 0 0 ...
## $ balance : int -111 -329 904 106 300 245 494 1774 1063 -191 ...
## $ housing : int 1 0 0 1 0 1 0 0 1 1 ...
## $ duration : int 19 13 36 67 8 7 16 14 141 674 ...
## $ previous : int 11 8 9 2 6 7 10 9 3 3 ...
## $ term_deposit: int 0 0 0 0 0 0 0 0 0 0 ...data1## ID age job marital education default balance housing duration
## 1 1 50 management 1 secondary 0 -111 1 19
## 2 2 41 technician 2 secondary 0 -329 0 13
## 3 3 36 entrepreneur 1 secondary 0 904 0 36
## 4 4 31 blue-collar 0 tertiary 0 106 1 67
## 5 5 51 unknown 0 primary 0 300 0 8
## 6 6 27 management 2 secondary 0 245 1 7
## 7 7 27 management 1 primary 0 494 0 16
## 8 8 59 entrepreneur 0 secondary 0 1774 0 14
## 9 9 43 retired 1 secondary 0 1063 1 141
## 10 10 46 technician 2 tertiary 0 -191 1 674
## 11 11 37 admin. 2 secondary 0 126 0 313
## 12 12 69 admin. 2 tertiary 0 840 0 128
## 13 13 48 technician 2 secondary 0 558 1 708
## 14 14 38 technician 2 primary 0 890 1 43
## 15 15 35 services 2 secondary 0 -151 1 96
## 16 16 58 retired 2 secondary 0 -382 0 398
## 17 17 36 admin. 2 primary 0 277 1 239
## 18 18 34 blue-collar 1 primary 0 496 1 173
## 19 19 33 retired 1 secondary 0 16649 1 173
## 20 20 41 services 0 secondary 0 4 1 232
## 21 21 31 blue-collar 1 tertiary 0 46 1 90
## 22 22 49 management 0 secondary 0 1162 0 159
## 23 23 37 blue-collar 0 tertiary 0 132 1 175
## 24 24 30 services 1 primary 0 296 0 41
## 25 25 54 retired 2 secondary 0 844 0 8
## 26 26 38 admin. 2 secondary 0 475 1 412
## 27 27 44 management 2 tertiary 0 309 1 676
## 28 28 37 entrepreneur 2 tertiary 0 57 0 345
## 29 29 30 management 1 secondary 0 2616 0 301
## 30 30 30 technician 1 secondary 0 574 0 11
## 31 31 26 technician 1 secondary 0 1018 0 101
## 32 32 59 management 2 secondary 0 242 0 17
## 33 33 50 admin. 0 secondary 0 381 0 519
## 34 34 29 blue-collar 1 secondary 0 0 1 16
## 35 35 31 management 1 secondary 0 334 1 195
## 36 36 35 technician 0 secondary 0 440 1 103
## 37 37 35 blue-collar 0 tertiary 0 500 1 177
## 38 38 33 technician 2 tertiary 0 741 0 283
## 39 39 56 admin. 2 secondary 0 5737 0 11
## 40 40 34 admin. 2 secondary 0 1072 0 136
## 41 41 59 services 2 primary 0 19102 0 462
## 42 42 45 management 2 secondary 0 900 1 508
## 43 43 41 blue-collar 2 primary 0 438 0 46
## 44 44 32 retired 2 secondary 0 1066 1 150
## 45 45 44 retired 2 secondary 0 794 1 342
## 46 46 53 admin. 2 secondary 0 264 1 159
## 47 47 50 self-employed 0 primary 0 388 0 701
## 48 48 39 technician 2 secondary 0 994 0 221
## 49 49 38 technician 1 tertiary 0 1819 0 101
## 50 50 36 management 0 secondary 0 3270 0 44
## 51 51 35 blue-collar 1 tertiary 0 2707 0 699
## 52 52 47 management 0 secondary 0 1815 1 105
## 53 53 29 management 2 secondary 0 503 0 433
## 54 54 31 admin. 1 secondary 0 430 0 129
## 55 55 31 technician 1 secondary 0 554 1 94
## 56 56 30 entrepreneur 1 primary 0 105 1 131
## 57 57 32 management 1 secondary 0 642 1 52
## 58 58 43 blue-collar 2 secondary 0 3529 0 169
## 59 59 30 blue-collar 1 secondary 0 293 1 232
## 60 60 34 services 1 tertiary 0 3 0 16
## 61 61 54 admin. 0 secondary 0 925 0 2
## 62 62 30 technician 1 primary 1 81 1 37
## 63 63 59 blue-collar 0 primary 0 7179 0 150
## 64 64 34 services 2 secondary 0 87 0 33
## 65 65 32 blue-collar 2 secondary 0 150 0 210
## 66 66 40 management 1 primary 0 -187 1 160
## 67 67 54 retired 2 tertiary 0 1544 0 85
## 68 68 50 management 0 secondary 0 223 0 221
## 69 69 55 technician 2 secondary 0 529 1 33
## 70 70 56 blue-collar 2 tertiary 0 14344 1 358
## 71 71 48 blue-collar 2 secondary 0 658 0 109
## 72 72 29 services 2 secondary 0 767 1 253
## 73 73 39 management 1 secondary 0 829 0 336
## 74 74 47 blue-collar 0 secondary 0 1565 0 253
## 75 75 38 technician 1 secondary 0 185 0 360
## 76 76 27 technician 1 tertiary 0 2648 0 917
## 77 77 27 blue-collar 1 secondary 0 11 0 257
## 78 78 32 services 2 tertiary 0 205 1 141
## 79 79 35 services 2 primary 0 4564 1 508
## 80 80 29 services 2 tertiary 0 204 1 307
## 81 81 37 admin. 1 secondary 0 123 0 136
## 82 82 36 services 1 tertiary 0 467 0 305
## 83 83 26 technician 1 secondary 0 101 1 810
## 84 84 39 admin. 2 primary 0 1846 0 306
## 85 85 57 self-employed 2 secondary 0 890 0 343
## 86 86 33 blue-collar 1 secondary 0 682 0 251
## 87 87 41 admin. 2 secondary 0 -378 1 361
## 88 88 26 technician 1 unknown 0 198 0 161
## 89 89 28 management 2 secondary 0 462 1 410
## 90 90 37 retired 2 secondary 0 2203 0 9
## 91 91 29 management 1 secondary 0 1562 1 286
## 92 92 33 technician 1 unknown 0 10600 0 202
## 93 93 47 admin. 1 primary 0 289 0 210
## 94 94 35 blue-collar 2 secondary 0 522 1 245
## 95 95 41 entrepreneur 2 tertiary 0 13874 0 255
## 96 96 26 management 1 secondary 0 598 1 401
## 97 97 33 blue-collar 1 secondary 0 1387 0 185
## 98 98 27 retired 2 secondary 0 616 1 263
## 99 99 45 technician 2 unknown 0 169 0 58
## 100 100 35 management 2 tertiary 0 1557 1 225
## 101 101 35 blue-collar 2 tertiary 0 429 1 143
## 102 102 35 blue-collar 0 tertiary 0 457 1 114
## 103 103 30 blue-collar 1 secondary 0 40 0 133
## 104 104 52 blue-collar 0 secondary 0 -57 0 140
## 105 105 36 technician 2 secondary 0 417 0 11
## 106 106 42 blue-collar 2 primary 0 -417 1 81
## 107 107 26 technician 1 tertiary 0 725 0 1916
## 108 108 26 admin. 1 secondary 0 685 0 388
## 109 109 29 retired 1 tertiary 0 991 0 563
## 110 110 28 management 1 tertiary 0 16 0 48
## 111 111 61 services 1 primary 0 433 0 346
## 112 112 49 technician 0 secondary 0 32 0 128
## 113 113 57 self-employed 2 secondary 0 7357 0 604
## 114 114 27 blue-collar 1 tertiary 0 2849 0 335
## 115 115 28 retired 1 secondary 0 1364 1 75
## 116 116 39 blue-collar 1 tertiary 0 917 1 161
## 117 117 50 admin. 2 secondary 1 -812 0 8
## 118 118 26 management 1 secondary 0 1242 1 205
## 119 119 27 management 1 secondary 0 424 0 248
## 120 120 29 technician 2 tertiary 0 241 0 7
## 121 121 36 technician 1 tertiary 0 351 0 82
## 122 122 26 blue-collar 2 primary 0 440 0 143
## 123 123 36 admin. 1 secondary 0 1598 1 208
## 124 124 28 services 1 secondary 0 1820 1 134
## 125 125 27 technician 1 secondary 0 923 0 139
## 126 126 30 technician 1 secondary 0 566 0 110
## 127 127 60 admin. 1 tertiary 0 361 0 1837
## 128 128 59 services 2 secondary 0 2740 0 130
## 129 129 29 blue-collar 1 primary 0 34 0 227
## 130 130 59 services 2 secondary 0 2613 0 79
## 131 131 59 management 2 secondary 0 201 0 52
## 132 132 41 admin. 0 secondary 0 8 0 92
## 133 133 31 technician 1 tertiary 0 96 0 577
## 134 134 34 admin. 2 primary 0 309 0 578
## 135 135 42 unemployed 2 secondary 0 2037 0 135
## 136 136 34 blue-collar 2 secondary 0 155 0 696
## 137 137 47 technician 0 primary 0 1927 1 130
## 138 138 42 services 2 secondary 0 -91 1 43
## 139 139 34 blue-collar 1 tertiary 0 0 0 71
## 140 140 37 blue-collar 2 secondary 0 7433 0 630
## 141 141 54 housemaid 2 secondary 0 883 0 305
## 142 142 57 self-employed 2 secondary 0 287 0 75
## 143 143 33 unemployed 1 secondary 0 238 1 45
## 144 144 31 blue-collar 2 secondary 0 1004 0 96
## 145 145 30 blue-collar 2 primary 0 935 1 96
## 146 146 36 services 1 secondary 0 159 0 443
## 147 147 42 blue-collar 1 secondary 0 541 1 656
## 148 148 56 unemployed 1 secondary 0 1187 1 47
## 149 149 40 services 2 secondary 0 632 0 611
## 150 150 60 blue-collar 2 tertiary 0 6684 1 173
## 151 151 34 blue-collar 1 secondary 0 1586 0 355
## 152 152 46 student 2 secondary 0 939 0 69
## 153 153 30 management 1 secondary 0 61 0 133
## 154 154 49 management 2 primary 0 217 1 537
## 155 155 30 technician 1 secondary 0 405 1 103
## 156 156 54 services 2 unknown 0 0 1 686
## 157 157 37 blue-collar 1 secondary 0 681 0 187
## 158 158 45 retired 1 secondary 0 33 0 437
## 159 159 56 blue-collar 0 secondary 0 1480 1 576
## 160 160 29 blue-collar 2 tertiary 0 4 0 156
## 161 161 41 services 2 tertiary 0 1143 1 134
## 162 162 48 technician 2 unknown 0 459 0 134
## 163 163 50 services 0 tertiary 0 -5 1 1118
## 164 164 35 blue-collar 1 unknown 0 186 1 196
## 165 165 27 technician 2 tertiary 0 312 0 251
## 166 166 34 admin. 1 primary 0 3648 1 288
## 167 167 32 management 2 tertiary 0 -149 0 93
## 168 168 33 technician 2 tertiary 0 26721 0 435
## 169 169 27 admin. 1 secondary 0 299 1 29
## 170 170 38 blue-collar 1 primary 0 3132 0 304
## 171 171 29 blue-collar 2 tertiary 0 476 0 148
## 172 172 34 services 0 tertiary 0 66 0 102
## 173 173 40 entrepreneur 2 secondary 0 18 1 166
## 174 174 34 retired 1 tertiary 0 84 0 231
## 175 175 29 admin. 1 tertiary 0 841 0 217
## 176 176 59 admin. 2 unknown 0 0 0 214
## 177 177 58 unemployed 1 secondary 0 -158 1 55
## 178 178 44 technician 2 secondary 0 320 1 269
## 179 179 56 services 2 secondary 0 121 0 151
## 180 180 36 management 2 primary 0 646 0 148
## 181 181 36 services 2 tertiary 0 0 1 245
## 182 182 29 technician 1 secondary 0 228 0 355
## 183 183 33 services 1 secondary 0 6106 0 345
## 184 184 40 technician 1 tertiary 0 265 0 121
## 185 185 27 admin. 1 tertiary 0 0 1 196
## 186 186 35 retired 1 tertiary 0 995 0 39
## 187 187 47 services 0 secondary 0 947 0 124
## 188 188 29 management 1 secondary 0 612 0 47
## 189 189 40 blue-collar 2 secondary 0 -212 1 71
## 190 190 41 management 1 secondary 0 618 0 1056
## 191 191 41 retired 0 secondary 0 110 1 76
## 192 192 33 management 1 secondary 0 406 1 61
## 193 193 33 management 2 tertiary 0 184 0 113
## 194 194 57 admin. 0 tertiary 0 442 0 41
## 195 195 33 blue-collar 1 secondary 0 3358 1 502
## 196 196 34 blue-collar 0 secondary 0 1281 0 237
## 197 197 53 services 2 tertiary 0 1624 0 158
## 198 198 49 technician 2 primary 0 1 0 98
## 199 199 27 management 1 tertiary 0 497 0 125
## 200 200 37 blue-collar 2 secondary 0 629 1 255
## 201 201 58 admin. 2 unknown 0 1617 1 109
## 202 202 33 self-employed 2 secondary 0 56 0 74
## 203 203 45 blue-collar 2 tertiary 0 2953 1 388
## 204 204 54 student 2 secondary 0 0 0 744
## 205 205 55 services 2 secondary 0 1765 1 445
## 206 206 30 services 1 secondary 0 728 1 393
## 207 207 42 management 2 secondary 0 315 1 208
## 208 208 45 management 2 secondary 0 925 1 118
## 209 209 34 services 0 tertiary 0 0 0 108
## 210 210 42 retired 2 secondary 0 513 0 98
## 211 211 45 blue-collar 2 secondary 0 858 0 617
## 212 212 38 retired 0 tertiary 0 915 1 22
## 213 213 34 housemaid 1 tertiary 0 992 1 71
## 214 214 36 services 2 tertiary 0 190 1 217
## 215 215 30 blue-collar 1 secondary 0 79 0 528
## 216 216 32 technician 0 secondary 0 2294 1 342
## 217 217 42 unknown 1 secondary 0 555 1 449
## 218 218 41 unemployed 1 tertiary 0 791 1 215
## 219 219 58 housemaid 2 secondary 0 0 1 1823
## 220 220 47 management 1 tertiary 0 178 0 17
## 221 221 35 unemployed 2 tertiary 0 137 0 142
## 222 222 40 blue-collar 2 primary 0 665 1 177
## 223 223 33 entrepreneur 0 tertiary 0 1 1 26
## 224 224 39 retired 1 tertiary 0 122 1 787
## 225 225 35 technician 1 secondary 0 1016 0 418
## 226 226 30 blue-collar 2 secondary 0 1743 1 192
## 227 227 28 management 1 tertiary 0 810 1 137
## 228 228 37 management 2 secondary 0 660 1 449
## 229 229 48 blue-collar 2 tertiary 0 500 1 53
## 230 230 29 services 1 secondary 0 209 0 605
## 231 231 55 blue-collar 2 secondary 0 956 1 116
## 232 232 27 services 1 secondary 0 126 1 147
## 233 233 48 entrepreneur 1 tertiary 0 318 1 1017
## 234 234 36 blue-collar 1 secondary 0 624 0 518
## 235 235 26 blue-collar 1 tertiary 0 449 1 339
## 236 236 31 blue-collar 1 unknown 0 643 0 82
## 237 237 29 admin. 1 secondary 0 401 1 127
## 238 238 33 blue-collar 2 tertiary 0 1099 0 111
## 239 239 55 admin. 2 tertiary 0 127 0 80
## 240 240 48 blue-collar 2 secondary 0 750 0 85
## 241 241 43 technician 2 primary 0 644 0 195
## 242 242 39 entrepreneur 2 tertiary 0 2976 0 134
## 243 243 48 admin. 2 secondary 0 426 1 153
## 244 244 38 technician 2 tertiary 0 0 0 214
## 245 245 40 management 2 primary 0 1908 1 1661
## 246 246 31 management 1 tertiary 0 2010 1 15
## 247 247 28 blue-collar 1 secondary 0 438 1 347
## 248 248 42 management 2 primary 0 4279 1 97
## 249 249 29 blue-collar 1 secondary 0 523 0 351
## 250 250 30 services 2 tertiary 0 285 0 693
## 251 251 28 admin. 1 secondary 0 1405 1 605
## 252 252 64 blue-collar 2 tertiary 0 6251 0 125
## 253 253 41 services 2 secondary 0 0 0 532
## 254 254 37 technician 2 tertiary 0 -491 1 80
## 255 255 57 management 2 secondary 0 3754 0 1063
## 256 256 31 blue-collar 2 unknown 0 68 1 425
## 257 257 60 entrepreneur 2 tertiary 0 2281 0 230
## 258 258 31 technician 2 secondary 0 823 1 152
## 259 259 46 services 2 tertiary 0 157 0 120
## 260 260 33 blue-collar 2 secondary 0 14850 1 122
## 261 261 36 blue-collar 2 secondary 0 696 1 590
## 262 262 28 management 2 tertiary 0 510 1 110
## 263 263 37 technician 2 primary 0 95 1 415
## 264 264 31 management 1 tertiary 0 544 0 401
## 265 265 25 entrepreneur 1 secondary 0 2354 0 226
## 266 266 42 student 0 tertiary 0 1775 1 276
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