SIMON FRASER UNIVERSITY 
STAT 485: Applied Time Series Analysis 
* Comprehensive Revision Guide and Course Notes 2024 
 
Part 01: Revision Notes 
Part 02: Sample Examination Paper 
Part 03. Suggested Solution to Exam Paper 
Part 04. Examination - Hints and Tips 
 
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Simon Fraser University - STAT 485: Applied Time Series Analysis

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ACADEMIC YEAR 2023 - 2024

University	Simon Fraser University
Study Level	Undergraduate
Course Code	STAT 485
Course Name	Applied Time Series Analysis
Notes Title	Comprehensive Revision Guide and Course Notes
Format	PDF
Page Length	71

* This comprehensive examination guide is designed for students enrolled in STAT 485: Applied Time Series Analysis at Simon Fraser University. It offers extensive coverage of all assessments throughout the course. Whether you are preparing for your assignments or the crucial midterm examination in 2024, this guide provides vital exam techniques and focuses on core questions relevant to your academic success. It features clear diagrams to enhance understanding and retention. This self-study resource is updated to reflect the latest course content, ensuring you are fully prepared for all academic evaluations.

Simon Fraser University's STAT 485: Applied Time Series Analysis course offers an in-depth introduction to linear time series analysis, covering moving average, autoregressive, and ARIMA models. It includes topics such as estimation, data analysis, forecasting errors, confidence intervals, conditional and unconditional models, and seasonal models. Prerequisites are STAT 260 and one of STAT 285, STAT 302, STAT 305, or ECON 333, with a minimum grade of C-. Students with credit for ECON 484 are not eligible. This is a quantitative course.

By the end of this course, you should be able to:

Understand the properties of moving average models.
Learn how to estimate parameters in moving average models.
Develop skills to make predictions using moving average models.
Comprehend the properties of autoregressive models.
Gain knowledge in estimating parameters for autoregressive models.
Acquire techniques for making predictions with autoregressive models.
Explore the combined properties of ARMA models.
Learn to estimate parameters and predict using ARMA models.
Understand and apply seasonal models for time series data.

COURSE CODE	COURSE NAME
BUS 232	Data and Decisions I
BUS 233	Introduction to Business Law and Ethics
BUS 251	Financial Accounting I
BUS 272	Behaviour in Organizations
BUS 312	Introduction to Finance
BUS 315	Investments
BUS 316	Derivative Securities
BUS 320	Financial Accounting: Assets
BUS 321	Financial Accounting: Equity
BUS 322	Intermediate Managerial Accounting
BUS 341	Fundamentals of Marketing
BUS 410	Financial Institutions
BUS 413	Corporate Finance
ECON 103	Principles of Microeconomics
ECON 105	Principles of Macroeconomics
ECON 201	Microeconomic Theory I: Competitive Behavior
ECON 233	Introduction to Economic Data and Statistics
ECON 333	Statistical Analysis of Economic Data
STAT 270	Introduction to Probability and Statistics
STAT 485	Applied Time Series Analysis

Simon Fraser University - STAT 485: Applied Time Series Analysis

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