UNIVERSITY OF GLASGOW 
STATS4037: Time Series 
Comprehensive Study and Exam Preparation Guide 2025 
 
Part 01: About This Guide 
Part 02: Sample Final Examination Paper 
Part 03: Detailed Solutions and Explanations 
Part 04: Proven Exam Strategies and Tips 
 
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University of Glasgow - STATS4037: Time Series (Solutions)

£25.00

ACADEMIC YEAR 2024 - 2025

University	University of Glasgow
School	School of Mathematics and Statistics
Course Code	STATS4037
Level	Level 4
Course Name	Time Series
Notes Title	Comprehensive Study and Exam Prep. Guide
Page Length	30

This guide provides you with an excellent opportunity to familiarise yourself with the content and format of the updated final examination for Time Series (STATS4037) - at the University of Glasgow in 2025. It also offers a chance to practise useful exam techniques. The guide focuses on core exam questions and includes clear, simple diagrams that facilitate understanding and recall during the real exam. Thoroughly updated, this self-study set covers all topics included in the latest edition of the course, ensuring students are fully prepared to tackle the final examination with confidence.

This course introduces students to the statistical modelling of time series data, focusing on three main aspects: identifying and modelling trends and seasonal patterns, analysing short-term correlations, and forecasting future observations. Students will learn to recognise key features in time series data using descriptive methods and explore different techniques to model trends and seasonality, comparing their effectiveness. The course also covers the theoretical properties of widely used models and demonstrates how to apply these models in practice.

By the end of the course, students will be able to determine the presence of trends, seasonality, or short-term correlation in a time series and understand the concept of stationarity. They will gain a solid understanding of ARIMA models, including how to assess whether these models are stationary and invertible, and how to derive their key statistical properties. Students will be able to select and fit an appropriate ARIMA model to real-world data, make forecasts, and use R to model time series in a way that accurately reflects the underlying data structure.

COURSE CODE	COURSE NAME
ACCFIN1001	Introduction to Business Reporting and Financial Accounting
ACCFIN1003	Finance 1
ACCFIN1004	Financial Accounting 1
ACCFIN1006	Introduction to Management Accounting and Control
ACCFIN1016	Introduction to Finance, Investments and Institutions
ACCFIN2002	Finance 2
ACCFIN2003	Financial Accounting 2
ACCFIN2018	Statistical Analysis and Methods
ACCFIN4010	Capital Markets and Portfolio Management
ACCFIN4040	Derivative Securities
ACCFIN4070	Corporate Finance
ACCFIN4079	Econometric Methods for Accounting and Finance
ACCFIN4081	Financial Management
ECON1001	Economics 1A
ECON1002	Economics 1B
ECON2001	Economics 2A
ECON2002	Economics 2B
ECON4003	Econometrics 1: Introduction to Econometrics
ECON4004	Econometrics 2: Multiple Regression and Applications
MGT1025	Current Topics in Marketing

University of Glasgow - STATS4037: Time Series (Solutions)

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