When arriving at the destination, the staff will check the goods again and record the damaged goods that occurred in transit. At the end of every month, we will pay for the compensation according to the number of the defective goods. In order to reduce the number of the damaged goods during the delivery, I want to identify the reasons why they are damaged. In this study, I want to find out that whether some drivers are more prone to make the goods damaged during their delivery.
Variable to be measured: Two variables are to be measured. The first variable is just the five truck drivers, and the second one is the quality of the goods after the delivery. Determination of Population: Population in this case is defined as the all goods delivered from Tianjin area to Guangzhou area. Statistical method: To analyze relationship between the two variables above which are both nominal in terms of data type, I decide to use Chi-squared test of a contingency table. Sample Selection:
Comparing the results, if the p-value is greater than 9. 49, there is not enough evidence to infer that there is a relationship between the five drivers and the number of damaged goods; if the p-value is not greater than 9. 49, I can reject the null hypothesis in favor of the alternative, which means there is a relationship between the five drivers and the number of damaged goods. So I can reduce the number of damaged goods through improving the drivers’ conditions.
