STATS 4A03 Time Series Analysis Project Guidelines
1 Objective
The objective of the this project is to demonstrate the time series analysis techniques we have discussed throughout the course by showing this project is similar to a common research paper. You are required to:
. Find a data set representing the observations of a time series. The total number of observations should be at least 50.
. Specify a tentative time series model for the data set.
. Estimate the parameters for the tentative model.
. Perform model diagnostic, then modify the model if necessary.
. Use the selected model for forecasting.
. Include the data set and the R package code. Identify the source of your data.
2 Presentation of Results
You must write a short scientiic report (in pdf format), which include the following components:
. Section 1: Introduction - Discuss the purpose, relevance, importance, and goal of the project, along with relevant background information on the topic.
. Section 2: Modeling - Explain the methods and techniques used to obtain the appropriate model. Use key plots and tables if necessary.
. Section 3: Results - Explain the efectiveness of forecasting and how it helps in reaching the goal proposed in the introduction.
. Section 4: Conclusion - Discuss the limitations of your results and potential future development.
. List of References.
3 Format
Your report must meet the following requirements:
. 12 point font in Times New Roman (or similar font).
. Single spaced.
. Number of pages of the report, including the title page and references: up to 10 pages.
. Up to 8 tables/plots in the report.
. The data set and the R package code must be uploaded separately from the scientiic report.
4 Resources for Data Sets
Some resources for inding data sets:
. Kaggle: https://www.kaggle.com/datasets
. UCI Machine Learning Repository: https://archive.ics.uci.edu
. Data.gov: https://data.gov
. Earth Data: https://www.earthdata.nasa.gov
. CERN Open Data Portal: http://opendata.cern.ch
. Global Health Observatory Data Repository: https://apps.who.int/gho/data/node.home
. Datahub.io: https://datahub.io/collections
. BFI Film Industry Statistics: https://www.bi.org.uk/industry-data-insights
5 Grading Rubric
To be added on Avenue to Learn..