Time Series Assessment
Introduction
This activity requires you to investigate time series data from Statistics New Zealand. You should base your statistical investigation and report on one of the three provided datasets:
Dataset 1: Number of Vehicle Registrations by Vehicle Type:
- Cars
- Rental Cars
- Trailers (including Caravans)
- Motor Cycles
Dataset 2: Value in millions of $NZ of Electronic Card Transactions by Goods Type:
- Consumables (e.g. fresh produce, detergents, lightbulbs)
- Durables (e.g. appliances, furniture, garden tools)
- Hospitality
- Services
- Apparel (clothing)
- Motor Vehicles
- Fuel
Dataset 3: Value in thousands of $NZof Imports by Regional Sea Port:
- Port of Auckland
- Port of Lyttelton
- Port of Tauranga
- Port of Wellington
- Port of Whangarei
All three datasets contain monthly data starting January 2006 to the most recently available month of data (either late 2016 or early 2017).
Assessment Conditions -
You will work independently over a period of 9 days to complete this task.
- You may not work on the assessment outside of class time.
- You may use your completed practice assessments and the achievement criteria as well as any other on-line resources to assist you in your investigation, however, your written work must be entirely your own.
- Any plagiarism will result in a Not Achieved grade.
- Any research and/or quotes that you use must be referenced.
- You may not share any of your work with anyone other than your teacher
- You must agree with your teacher the method that you will use to communicate your work with them and their feedback to you.
Your Task -
Complete a statistical investigation on one of the three datasets provided.
As a guide you should undertake the following steps:
1. Familiarise yourself with the data set. This should include doing further research to help you understand the variables and to develop a purpose for the investigation.
2. Detail the purpose of your investigation and select at least one of the variables in one dataset to investigate.
3. Select and use appropriate display(s) to graph your data using iNZight.
4. Investigate and discuss the overall trend and seasonal effects.
5. Discuss how well the fitted modelfits with the raw data, including analysis of residuals.
6. Use your fitted model to make a forecast. Discuss upper and lower bounds. Evaluate the adequacy of the fitted model and consider the validity of your forecast.
7. Conclude your investigation. Support your conclusion by referring to your research and your analysis and/or features of the visual displays. Include a reflection on your process, which could consider other relevant variables.
8. In writing your report, link your discussion to the context and support the statements you make by referring to statistical evidence (numerical) and the research you have undertaken.
Attachment:- Assignment Files.rar