E-commerce and online shopping are creating a rapidly growing demand for parcel
delivery services. The key factors of customers’ satisfactions are both the speed and
frequency of delivery which require more efficient flow of parcels through the
transportation. To help improve its transportation network performance, a private
postal service in North America conducted a survey to analyze the relationship
between delivery results (1: on-time and 2: late) and transportation mode (1: regular,
2: express, and 3: weekend delivery). A sample of 70 deliveries was asked from the
sale department. Data can be found in the Excel file AS4.XLSX (Ecom) in the Excel
directory. Do these data allow us to infer that the delivery results are affected by the
transportation mode (5% significance)?
Delivery result | |
Transportation mode | Delivery Result |
Express | On-Time |
Weekend Delivery | Late |
Express | On-Time |
Regular | On-Time |
Regular | On-Time |
Weekend Delivery | On-Time |
Weekend Delivery | Late |
Weekend Delivery | On-Time |
Regular | On-Time |
Express | Late |
Express | Late |
Weekend Delivery | Late |
Express | On-Time |
Regular | On-Time |
Regular | On-Time |
Regular | On-Time |
Regular | On-Time |
Express | On-Time |
Weekend Delivery | Late |
Regular | On-Time |
Regular | On-Time |
Regular | On-Time |
Weekend Delivery | Late |
Regular | On-Time |
Regular | On-Time |
Weekend Delivery | On-Time |
Weekend Delivery | Late |
Regular | On-Time |
Regular | On-Time |
Weekend Delivery | On-Time |
Express | Late |
Express | On-Time |
Regular | On-Time |
Regular | On-Time |
Express | On-Time |
Weekend Delivery | Late |
Weekend Delivery | Late |
Weekend Delivery | Late |
Regular | On-Time |
Regular | On-Time |
Regular | On-Time |
Regular | On-Time |
Weekend Delivery | Late |
Regular | Late |
Regular | On-Time |
Express | Late |
Weekend Delivery | Late |
Regular | On-Time |
Regular | On-Time |
Express | On-Time |
Express | Late |
Weekend Delivery | Late |
Express | Late |
Regular | On-Time |
Regular | On-Time |
Weekend Delivery | On-Time |
Express | Late |
Regular | On-Time |
Weekend Delivery | On-Time |
Weekend Delivery | On-Time |
Weekend Delivery | Late |
Weekend Delivery | Late |
Regular | On-Time |
Regular | On-Time |
Weekend Delivery | On-Time |
Express | On-Time |
Express | On-Time |
Weekend Delivery | On-Time |
Express | On-Time |
Regular | On-Time |
This is chi-square test of independence
install.packages("readxl")
library(readxl)
delivery = read_excel("../Tutoring/Software/random
data/delivery.xlsx")
tbl <- table(delivery$`Transportation mode`,delivery$`Delivery
result`)
tbl
chisq.test(tbl)
since p-value = 0.0000277 < alpha(0.05)
hence we reject the null hypothesis
we conclude that there is sufficient evidence that the delivery results are affected by the transportation mode
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