Reference no: EM132519731
MIS171 Business Analytics - Deakin University
Learning Outcome 1: Apply quantitative reasoning skills to analyse business problems.
Learning Outcome 2: Create data- driven/fact-based solutions to complex business scenarios.
Learning Outcome 3: Implement contemporary data analysis tools to analyse business performance.
General Description / Requirements -
This is an individual assignment and it focuses on materials presented up to and including Week 9.
To complete the assignment you should:
- Analyse the dataset to answer the specific questions presented to you during the online test (see the scenario below);
- Interpret the results, and draw conclusions.
Once you have done this, you will have the necessary output (i.e., data analysis , related summary information , and relevant visualisations) to complete the online test . The test contains fifteen (15) randomly allocated multiple- choice questions related to your data analysis, its interpretation, and your subsequent conclusions. The assignment uses the file MIS171- 2020- T 1- A 3 .xlsx which can be downloaded from CloudDeakin.
Scenario - The Leonard's is a Korean restaurant chain founded in 2017 that specialises in Korean fried chicken and beer. Leonar d's has three branches in Australia (Melbourne, Sydney, and Canberra). Their product range includes different types of fried chicken, Korean rice, burgers, salads, beer and beverages, and desserts.
You are Anthony Mcpel, a business analyst who works for the Leonard's in their Research and Analysis department. You have received an email from the Head of Analytics, Nimish Rayan, asking to perform some data analysis on a dataset provided to you. The email making this request alongside some guidelines (in blue) is presented below. Consider these comments carefully.
The senior management team is awaiting reports on the following projects:
1. Project 1: Leonard's customers' spend analysis
The data set includes a random sample of 400 Leonard's customers. Build a multiple regression model to predict the amount spent per transaction. Your model should provide insights into what factors influence spent amount per transaction as well as the ability to predict spent per transaction for various scenarios.
For this analysis, you will need to build a multiple regression model using Spend per transaction as the dependent variable. You should follow the model building process introduced in the lecture and tutorial. To select variables to include in the model, start with transforming categorical variables into dummy variables. When transforming city into dummy variables, consider Sydney as the baseline category; meaning the created dummy variables for city should only include Melbourne (Yes and No), and Canberra (Yes and No). Then, create scatter diagrams and calculate relevant model summary coefficients. Afterwards, run the multiple regression analysis and assess the model for overall significance (F test with alpha set at 0.05). In the next step(s), if the overall model is found to be significant, in a stepwise fashion, remove variables that are least likely to be contributing to any significant change in the dependent variable one at a time (if there are any), by conducting a series of t -tests with alpha set at 0.05.
2. Project 2: Leonard's profit analysis
Data on Leonard's monthly sales from January 2 018 to March 2020 is provided. Leonard's management team is interested in forecasting profit, as they believe there is a time-based pattern in the sales values. Implement a proper forecasting model to address this request and provide your interpretation.
For this study, you need to consider several forecasting models and evaluate model performance in terms of forecasting accuracy and model fit. You should consider the following:
(a) Both 3 and 5 periods centred moving average models.
(b) Fitting linear, exponential, logarithmic, polynomial (order 2), and power trend lines to the original data.
(c) What do the errors say about the usefulness of the forecasting models?
(d) What are the R2 values of the models?
(e) What would be the forecasted profit for the next nine -time period s (April 2020 to December 2020) using each of the models you have built?
Attachment:- Business Analytics Assignment Files.rar