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MIS771 Descriptive Analytics And Visualisation

tag 0 Download 5 Pages / 1,181 Words tag 16-07-2021

Question:

Task 1 – Summarising Dependent Variables

The purpose of this task is to analyse and explore key features of these two variables individually.
At very least, you should thoroughly investigate relevant summary measures of for these two variables. Proper visualisations should be used to illustrate key features of these two variables.
Your technical report should describe ALL key aspects of each variable.

Task 2.1. – Identifying relevant factors for predicting customer satisfaction

Analyse the relevant dependent variable against other variables included in the dataset. Your job is to decide which variables to include here. Use an appropriate technique to identify important relationships.
The outcome of this task is a list of variables that should be included in the subsequent analysis. Your technical report should describe why some variables were selected while others were dropped from subsequent analyses.

Task 2.2. – Model Building (Predicting Customer Satisfaction)
 
You should follow model building process outlined in Module 2 – Topic 2. All steps of model building process should be included in your analysis. You can have as many Excel worksheets (tabs) as you require to clearly demonstrate different iterations of your predictive model (i.e., 2.2.a., 2.2.b., 2.2.c. etc.). 
Your technical report should clearly explain why the model may have undergone several iterations.
Also, you must provide detailed interpretation of ALL elements of the final model.

Task 2.3. – Interaction Effect

To accomplish this task you need to develop a regression model using ONLY factors discussed in the ‘minutes of the meeting – Task 2.3.’. In other words, this section of analysis is separate from the regression model constructed in Task
 
2.2. Your technical report should clearly explain the role of each variable included in the model. A proper visualisation technique should be used. Make sure you interpret all relevant outputs in detail and provide managerial recommendations based on the results of your analysis.

Task 3.1. – Model Building (Likelihood of Building Strategic Alliance/Partnership) You should start building the predictive model by including ONLY the variables listed in the ‘minutes of the meeting –
 
Task 3.1.’. You are required to demonstrate all iterations of your predictive model. Note that your final model should only include those variables that have predictive value. Your technical report should clearly explain why the model may have undergone several iterations. A detailed interpretation of ALL elements of the final model must be provided.
 
Task 3.2. – Visualising and Interpreting Predicted Probabilities

Your technical report must include the predicted probability visualisation and be supplemented by practical recommendations to Hugo Barra (or AusPaper). These recommendations should answer the following question:
“How change product quality (scores from 0 to 10) and price flexibility (scores of 0, 5, and 10) may affect the predicted probability of building strategic alliance with AusPaper for customers who have neutral feeling (fixed score of 5) towards personnel image and product line?”

Task 4. – Forecasting Turnover
AusPaper’s quarterly turnover from quarter one 2008 to quarter one 2017 are given in the AusPaper_Turnover worksheet. Your job is to develop a proper forecasting model to predict turnover for the next three quarter (i.e. Q2 to Q4 2017).

In your technical report, you must explain the reason for selecting the forecasting method to predict future turnover. The report also must include a detailed interpretation of the final model. (e.g. a practical interpretation of the time-series model, choices about smoothing technique etc.).
 
Task 5. – Technical Report
Your technical report must be as comprehensive as possible. ALL aspects of your analysis and final outputs must be described/interpreted in detail. Remember, your audience (i.e., Hugo) is an expert in Analytics and he expects nothing but perfection from your report. Perfection means quality content (demonstrated attention to details) as well as an aesthetically appealing report.
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[Accessed 03 February 2023].

My Assignment Help. 'MIS771 Descriptive Analytics And Visualisation' (My Assignment Help, 2021) <https://myassignmenthelp.com/free-samples/mis771-descriptive-analytics-and-visualisation/identifying-customer-satisfaction.html> accessed 03 February 2023.

My Assignment Help. MIS771 Descriptive Analytics And Visualisation [Internet]. My Assignment Help. 2021 [cited 03 February 2023]. Available from: https://myassignmenthelp.com/free-samples/mis771-descriptive-analytics-and-visualisation/identifying-customer-satisfaction.html.


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