To accomplish allocated tasks, you need to examine and analyse the dataset (supermart.xlsx) thoroughly. 

Below are some guidelines to follow:

Task 1 – Summarising Dependent Variables

The purpose of this task is to analyse and explore key features of these variables individually. At the 

very least, you should thoroughly investigate relevant summary measures/charts and graphs of 

these variables. Proper visualisations should be used to illustrate key features. 

Your technical report should describe ALL key aspects of each variable.

Task 2. – Model building (predicting Sales)

You should follow an appropriate model building process. All steps (including pre and post model 

diagnostics) of the model building process should be included in your analysis. You can have as 

many Excel worksheets (tabs) as you require to demonstrate different iterations of your regression 

model (i.e., 2.2.a., 2.2.b., 2.2.c. etc.). You must make reasonable/realistic/practical assumptions 

about the parameters you are working with in Task 2.

Your technical report should clearly explain why the model might have undergone several 

iterations. Also, you must provide a detailed interpretation of ALL elements of the final

model/regression output.

Task 3. – Interaction effect

To accomplish this task, you need to develop a regression model using ONLY the factors discussed 

in the meeting (Task 3). In other words, this section of analysis is separate from the regression 

model constructed in Task 2. You must make reasonable/realistic/practical assumptions about the 

parameters you are working with in Task 3.

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 4 – Model building (likelihood of a store opening on Sunday)

You should follow an appropriate model building process. All steps (including pre and post model 

diagnostics) of the model building process should be included in your analysis. You can have as 

many Excel worksheets (tabs) as you require to demonstrate different iterations of your regression 

model. You must make reasonable/realistic/practical assumptions about the parameters you are 

working with in Task 4.

You are required to discuss all details of your predictive model/logistics regression output.

MIS771 - Descriptive Analytics and Visualisation Trimester 2, 2019

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Task 5.1 – Model building (likelihood of a store opening an online sales channel)

You should start building the predictive model by including ONLY the variables listed in the ‘minutes 

of the meeting – Task 5.1’. You must make reasonable/realistic/practical assumptions about the 

parameters mentioned in Task 5.

You are required to discuss all details of your predictive model.

Task 5.2. – Visualising and interpreting predicted probabilities

Your technical report must include the predicted probability visualisation and be supplemented by

practical recommendations to Superstore’s Management.

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