| Category | Assignment | Subject | Business |
|---|---|---|---|
| University | Monash University (MU) | Module Title | ETF1100 Business Statistics |
Energy Consumer Australia is an independent organization representing energy consumers from the residential and small business owners. One of its projects is to conduct bi-annual Energy Consumer Sentiment survey. This data can be used to help retail energy providers to understand the attitudes of energy consumers and the drivers of their intention to switch companies.
In your tutorial exercises, you would have conducted some simple analysis of the driver of the intention to switch. One key driver identified is that customers who intend to switch respond with low overall customer satisfaction score (OverallCSE). In this assignment, your task is to investigate and report how the overall customer satisfaction score is associated with other aspects of customer satisfaction (bill, value for money), as well as some basic customer demographics.
In the file “Group Assignment Data.xlsx”, you are provided with both numeric and categorical data that were collected as part of the survey. Note that this data has already been cleaned for you, and any missing records are removed. Only residential energy consumer responses are provided.
The following table contains the data definition.
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[Note that you will be conducting a number of these analyses as part of the tutorial exercises from week 7 onwards.]
Segment your data into two groups: Customers who indicated that they intend to switch providers and customers who reported that they did not intend to switch providers.
1a Conduct a hypothesis test to assess whether the mean overall satisfaction of customers who do not intend to switch provider is smaller than 8.25.
1b Conduct a hypothesis test to assess whether the mean overall satisfaction of customers who intend to switch provider is smaller than 8.25.
1c Compare your results from 1a and
1b. Provide an analysis of how overall customer satisfaction score is related to their intention to switch.
Use the appropriate Excel tool (Data filter or pivot tables) to analyze the relationship between “Switch” and “BillLargerThanExp”.
2a Calculate the proportions of customers who responded “Yes” to “BillLargerThanExp”, segmented by whether or not they intend to switch providers. Comment on the difference in the two proportions. You may use the concept of confidence intervals to aid your analysis.
2b From past surveys, the typical observation is that 1/3 of customers find their bill larger than expected. Is there statistical evidence to suggest that this proportion is underestimated in those who intend to switch providers? How does this compare to those who do not intend to switch providers? Support your answer with hypothesis tests of proportions.
Investigate the relationship between the overall satisfaction score (OverallCSE6mth) and the other satisfaction scores (VoMSat and BillSat) using correlation statistics and single regression models.
Note that while the satisfaction scores are strictly ordinal categorical variables, we treat them as numerical in a regression setting as the number of categories is large and we can interpret the results according to the data definition scale.
3a Estimate the single regression model of OverallCSE6mth on VoMSat. Interpret the slope of VoMSat.
3b Estimate the single regression model of OverallCSE6mth on BillSat. Interpret the slope of BillSat.
For this task, focus on the following variables as explanatory variables to the overall satisfaction score:
4a Convert the variables “OwnorRent”, “Gender” and “Bill LargerThanExp” into dummy variables. Construct the dummy variables using the following definitions:
4b Estimate the multiple regression model with “Overall CSE6mth” as the dependent variable (Y), with the following explanatory variables (X):
4c Analyze the slope coefficients from the model you estimated in 4b. Interpret and report on the slope coefficients of this model. including commentary on the statistical significar Why is this page out of focus?n the model to analyze the key drivers of Overall CSE6mth. Because this is a premium document. Subscribe to unlock this document and more.
Are they different? If so, why do you think they are different? Comment on the goodness of fit of the multiple regression model compared to the simple regression models from Task 3 based on the regression model statistics.
Based on your statistical analysis from Tasks 1-4 above, write a report discussing the following items:
The maximum total mark for the assignment is 100. Your total score will be composed of two parts:
The Chief Examiner reserves the rights to adjust individual report marks based on the peer evaluation. Should the feedback indicate that an individual did not contribute to the group assignment, the report mark will be adjusted to zero, implying that the individuals group assignment contribution to their final grade will be 0%.
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