Reference no: EM132370611 , Length: word count : 1000

Research Report Group Assignment

This assignment uses data from the BUPA health insurance call centre. Each observation includes data from one call to the call centre. The variables describe several characteristics of the call (eg the length of the call, the amount of silence in the call), characteristics of the customer (eg state of residence, family type, number of adults and children), and measures of performance (eg net promoter score, sentiment score of the customer). In this assignment we are interested in predicting the net promoter score and the length of the call.

Please use the dataset CallCentre.dta and associated information file CC_DEFINITIONS_.XLSX to answer these questions. Use the software program STATA 15 available through RMIT MyDesktop for all data analysis.

1. Calculate descriptive statistics using the ‘summarize’ command for the variables net_promoter_score, total_silence,total_silence_weighted, agent_to_cust_index and agent_crosstalk_weighted and present the results in a table. Comment on what we learn about these variables from the descriptives. Graph a scatter plot of net_promoter_score  against agent_crosstalk_weightedand describe the relationship between these two variables.   

2. Estimate a multiple linear regression with net_promoter_score as the dependent variable and total_silence_weighted, agent_to_cust_indexand agent_crosstalk_weightedas the explanatory (independent) variables. Predict the change in net_promoter_score associated with a 0.1 increase in total_silence_weighted and a 0.01 increase inagent_crosstalk_weighted.Assuming this is the correct model specification, are we sure that total_silence_weighted has a negative effect? [Hint: consider the t-statistic and p-value]

3. Add dummy variables to the regression to control for all of the potential effects of State and Package. Make sure the base category is customers with the “HOSPITAL AND EXTRAS” package in NSW. Carefully interpret the estimated coefficient on the package1 dummy variable you have included. Why is this NOT a very important result?

Attachment:- Assignment Data Files.rar