Statistics essay

Lesson 3 Essay

GBS 211-Business Statistics

Rio Salado College

Lesson 3 Essay: Call Errors

According to the information of Quality Summary and Call Center Data, I summary some details about the vice president. Therefore, in this paper, I will talk about the relative frequency for overall type of calls, call quality, and call errors. Moreover, descriptive statistics for call time will be mentioned. Furthermore, some probabilities will be provided. I will also base on the data, pointing out which error should be focus on. Finally, evaluating the current call time is significant.

According to the Quality Summary and Call Center Data, we are able to easily calculate the relative frequency for all type of calls, call quality, and call errors. Firstly, overall incoming calls by type is demonstrated more clear. For example, the relative frequency of Check coverage of policy is around 0.268, Check status of claim is around 0.237, Update address is about 0.196, File a claim is about 0.141, Update information on claim is about 0.065, Update Policy is around 0.054, Cancel Policy is about 0.040. Secondly, Call Quality is also showed pretty obvious. The relative frequency of Correct call is 0.85, and Incorrect Call is 0.15. We can easily notice that incorrect call still makes up a big part. Eventually, Call Errors are also divided by several parts. Incorrect coverage quote (COV) makes up the largest part, its relative frequency is 0.36. The relative frequency of Incorrect capture of claim (CLM) is 0.28. Likewise, did not transfer to “Save a Policy” (SAV) is around 0.213. Finally, Incorrect claim status provides (STAT) has the lowest relative frequency, which is around 0.147.

Additionally, when we analyze the descriptive statistics of call time, we can draw a conclusion. The mean of the call time is 11.07 minutes, the median is 10.63 minutes, the mode is 12 minutes, variance is around 11.449, the standard deviation is about 3.834, and the range of the call time is 14.25. It is obvious that after using the descriptive statistics, we have the ability to see the characteristics of the call time more direct than just looking for the whole data.

What is more, after the calculating, we can illustrate each probabilities of the information, such as CLM, COV, SAV, STAT, AM, and PM. First of all, the probability of CLM Error and AM Shift is 0.14. Secondly, the rate of COV Error and PM Shift is 0.18. And then, the probability of SAV Error or AM Shift is around 0.6065. Finally, given that the call comes in the morning, 0.5 is the probability of a CLM Error.

P (CLM Error and AM Shift) = P (CLM Error) * P (AM Shift) = 0.28*0.5 = 0.14

P (COV Error and PM Shift) = P (COV Error) * P (PM Shift) = 0.36*0.5 = 0.18

P (SAV Error or AM Shift) = P (SAV Error) + P (AM Shift) – P (SAV Error and AM shift) = 0.213+0.5-0.213*0.5= 0.6065

P (AM Shift/CLM Error) = P (AM Shift and CLM Error)/P (CLM Error) = (0.5*0.28)/0.28 = 0.5

In conclusion, based on the data, Incorrect Coverage quote (COV) has the highest probability that might be happened. Therefore, the team should focus on the Incorrect Coverage quote (COV). In my point of view, I convinced that shift does no matter. Because of that the AM Shift and the PM Shift both make up the half the whole data, they do not influence the results.

According to the date, we are able to easily realize that the majority of the call time around 7.5 minutes are AM Shift. As the result, we can predict that the current call time is AM Shift.