DATA4400 Assignment Help

Subject Code: DATA4400
Subject Name: Data-driven Decision Making and Forecasting
Assessment Title: Evaluating forecasting-based analytics
Assessment Type: Individual Report
Word Count: 1000 Words (+/-10%)
Weighting: 30%
Total Marks: 30
Submission: Turnitin
Due Date: Tuesday, Week 10 23.55pm AEST

Your Task

Given a dataset with multivariate time series data, you are to conduct multiple forecasting methods and provide a description and interpretation of the techniques used. The report is worth 30 marks (see rubric for the allocation of these marks).

Assessment Description

A dataset will be provided to you at the beginning of week 9. The objective of the assessment is to build different forecasting models using Orange Data Mining and Tableau. Students must calculate the Root Mean Square Error (RMSE) or Mean Absolute Percentage Error (MAPE) to evaluate the performance and accuracy of the model, as well as choose the appropriate metrics for model selection.

Assessment Instructions

Report Structure and Content

Imagine you work for the Central Bank of Genovia and your task is to forecast the  unemployment rate in one quarter.  

  1. Import the DATA4400_A2_Data.csv dataset into Orange Data Mining  ( 
  2. Assess the quality of the data in terms of missing values and provide summary statistics  of the variables. 
  3. Using an ARIMA model, forecast the unemployment rate for one quarter. (A) What is the forecast unemployment rate based on the ARIMA model? b. Provide a screenshot of the ARIMA model settings and the appropriate  visualisation for your forecast. 
  4. Using a VAR model, forecast the unemployment rate for one quarter. (A) What is the forecast unemployment rate based on the VAR model?  (B)Provide a screenshot of the VAR model settings and the appropriate visualisation  for your forecast. 
  5. How do the Fed Funds rate and the unemployment rate affect each other in Genovia? 
  6. Use Tableau ( to visualise the dataset and  generate a forecast of the unemployment rate at the end of the next quarter. 
  7. What is the unemployment rate forecasted by Tableau? 
  8. Explain which model was used in Tableau and report on its parameters. 
  9. Evaluate the models using the available metrics and report which model provides the  best forecast.
  10. Summary

Important Study Information 

Academic Integrity Policy 

KBS values academic integrity. All students must understand the meaning and consequences  of cheating, plagiarism and other academic offences under the Academic Integrity and Conduct  Policy. 

What is academic integrity and misconduct? 

What are the penalties for academic misconduct? 

What are the late penalties? 

How can I appeal my grade? 

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Word Limits for Written Assessments 

Submissions that exceed the word limit by more than 10% will cease to be marked from the  point at which that limit is exceeded. 

Study Assistance 

Students may seek study assistance from their local Academic Learning Advisor or refer to the  resources on the MyKBS Academic Success Centre page. Click here for this information.

Assessment Marking Guide

Standards for this Task Points
Forecasting Results

  • Loaded data into Orange and identified relevant widgets.
  • Identified information that is relevant to building the required models.
  • Able to identify information relevant to facilitate the understanding of ARIMA and VAR models.
  • Developed models and created forecasts.
  • Adequately identified variables causing unemployment rate.

  • Compared results with outputs from a BI tool and/or Exploratory
  • Included a figure of Orange workflow with explanation of the output.
  • Identified any inconsistencies in output.
  • Provided interpretations that are within the scope of the subject and assessment.
Report and Summary:

  • Structured such that the reader can grasp key points from the analysis.
  • Key headings are included.
  • Justification of assumptions and interpretations are clear and concise.
  • In-line referencing used and references are relevant and genuine.
  • Visualisations are used to convey key arguments.