Assignment Task
Task
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Get Help Now!This assignment requires you to analyse a data set (including performing a multiple regression analysis), interpret, and draw conclusions from your analysis. You are required to explain the Summary Output from your multiple regression analysis in a written report, which must also include TWO recommendations to the RACV Board. The assignment must be completed individually and submitted electronically in CloudDeakin by the due date. When submitting electronically, you must check that you have submitted the work correctly by following the instructions provided in CloudDeakin. Hard copies or assignments submitted via email will NOT be accepted.
The assignment uses the file 2022 T1 RACV Solar Data Set A3.xlsx which can be downloaded from CloudDeakin. The assignment focuses on materials presented up to and including Week 11. The data set is based on actual data provided by RACV Solar. For confidentiality and anonymity reasons actual data has been manipulated in the assessment task. Following is an introduction to this scenario and detailed guidelines.
Assignment instructions:
The assignment consists of two parts.
Part 1: Data Analysis:
Your data analysis must be performed on the Assignment 3 Excel file. The file includes tabs (spreadsheets) for:
• Data Description
• RACV Solar Data Set
• Analysis for Question 1
• Correlation, which includes:
- Creating Dummy variables,
- Creating a correlation table,
- Eliminating uncorrelated Independent Variables, and
- Eliminating IVs where multi-collinearity is present
• Model – building the regression model, including multiple iterations, and
- Reporting the Summary Output of the final regression model,
- Identifying the final equation, and explaining/interpreting the final equation, and
- Calculating and explaining the Point Estimate, Prediction Interval, and Confidence Interval for the scenario provided.
When conducting the hypothesis tests you need to follow the steps outlined in the lecture and seminars, including appropriate conclusions.
When performing the multiple regression carefully follow the steps outlined in the lecture and seminars, and set out in the steps (in blue) in James’s email.
The only worksheets in the Excel file provided by James that will be marked are Q.1, Correlation, and Model. Follow the steps (in blue) in James’s email for what to include in the reporting sections that will be marked (e.g. Output and Conclusion sections in the different worksheets). There should be no need to create additional worksheets.
Make sure your analysis and process complete, clear, and easy to follow. You may need to add (or widen/narrow) rows or columns to present your analysis clearly and completely. Poorly presented, disorganised analysis or excessive output will be penalised.
Part 2: Report:
Your report is to be addressed to James Wright. The report is to be split into two sections. In the first section it is expected that you will use technical terms such as “hypothesis test”, “coefficient of determination”, “standard error”, and “adjusted R square”, etc. You can assume that James is familiar with all these terms.
In the second section please assume that James will send Section 2 of your report directly to the RACV Solar Board. Your language must be appropriate for a professional audience that has no formal training in business analytics. This means that you must use plain, straight-forward, and easily understand language.
Section 1.
Section 1 will only be read by James Wright. James has training in business analytics and understands technical terms. Having completed your regression analysis of the RACV Solar data set and created your final regression model, the first section of your report requires an explanation of the Summary Output of your final regression analysis, including (but not limited to) the different values in the Regression Statistics, the significant variables, the regression coefficients, Significance F, and the different Pvalues.
Section 2.
Make TWO (2) recommendations that RACV Solar could consider to maximise revenue (i.e., maximise the value of System Cost). Location, System Size and Client Satisfaction should be considered in drafting one or other of your recommendations. However, other variables should be considered and could be included in one or other of your recommendations. Your recommendations can be based on analysis in this assignment, analysis from previous assignments and any other analysis that you consider is relevant and adds impact to your recommendations. Highest marks will be awarded to students whose recommendations are clearly expressed.
Learning Outcomes:
This task allows you to demonstrate achievement towards the unit learning outcomes (ULOs). The ULOs are aligned with specific graduate learning outcomes – that is, the skills and knowledge graduates are expected to have upon completion of their studies – and this assessment task is an important tool in determining achievement of those outcomes. If you do not demonstrate achievement of the unit learning outcomes, you will not be successful in this unit.
It is good practice to familiarise yourself with the ULOs and GLOs as they provide guidance on the knowledge, understanding and skills you are expected to demonstrate upon completion of the unit.
In this way they can be used to guide your study.
Unit Learning Outcomes:
ULO1: Apply quantitative reasoning skills to analyse business problems.
ULO2: Create data-driven/fact-based solutions to complex business scenarios.
ULO3: Analyse business performance by implementing contemporary data analysis tools.
ULO4: Interpret findings and effectively communicate solutions to business problems
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