MIS771: Descriptive Analytics and Visualisation - Apply Quantitative Reasoning Skills - Engineering Assignment Help

Assignment Task :

ULO 1: Apply quantitative reasoning skills to solve complex problems. 

ULO 2: Plan, monitor, and evaluate own learning as a data analyst. 

ULO 3: Deduce clear and unambiguous solutions in a form that they useful for decision making and research purposes and for communication to the wider public. 

The Case Study 

ANALYTICs7, a leading data analysis consulting company, has extensive experience in analysing data for both local and global, small to medium companies. By solving their business problems, ANALYTICs 7 helps these businesses to plan ahead and thrive. 

Your Role in ANALYTICS7 Dr Hugo Barra, the lead data scientist at ANALYTICs7 has engaged you to lead the modelling component for the TPM and AP projects and construct a report of your key findings and recommendations in response to the questions posed in the meeting minutes of the last team meeting on the next page. 

Datasets 

There are two datasets available for this assignment: TPM_Employee_Attrition and Monthly_EnergyCon_MW 

Employee Survey data (TPM_Employee_Attrition )– TassPaperMill (TPM), a subsidiary of Pinnon Paper Industries (PPI), is an Australian company with a long history of manufacturing paper rolls. To address numerous concerns raised in their recent employee survey TPM is currently reviewing how they calculate salary increments for their employees. TPM has hired ANALYTICs7 to extract a random sample of 1470 employee records from their HR database. Their ultimate goal is to adopt a more holistic rewarding system factoring the key relations between remuneration indicators and demographic characteristics, employment history and various other potential contributors to boost performance. In addition, human resource manager at TPM reported in her recent presentation to the company executive management team that the staff turnover rate at TPM is higher compared to their competitors. Thus, TMP wants to identify key contributing factors before they lose more talented, motivated and focused employees who contribute to the organisation's overall success. 

Discussion items:

1. Variable(s) description 

2. Modelling PercentSalaryHike 

3. Modelling the likelihood of an employee leaving the company 

4. Forecasting monthly energy consumption in Megawatts 

5. Producing a technical report 

Detailed Action Items 

Who: 

Modeller 

What: 

1. Providing an overall summary of the following two variables: 

1.1. Percentage increase in salary (PercentSalaryHike) 1.2. Attrition 

2. Identify potential variables that may influence PercentSalaryHike: 

2.1. Identify a list of possible variables that influence percentage increase in salary. Which three independent variables have the more impactful linear relationship with PercentSalaryHike? What form of relationship(s) exist between the independent variable(s) and PercentSalaryHike? Are there any potential multi-collinearity problems? If so, which variables are they? 

2.2. Build a regression model to estimate percentage increase in salary. 

2.3. Perform residual analysis. Based on your residual plots, does there appear to be any problems with the regression model? 

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