Time Series Analysis (Intensive)

Prerequisites

This module introduces the time series techniques relevant to forecasting in social science research and computer implementation of the methods. Background in basic statistical theory and regression methods is assumed. Topics covered include time series regression, moving average, exponential smoothing and decomposition. The study of applied work is emphasized in this non-specialist module.

This module is designed for MPhil and PhD students as part of the Social Science Research Methods Centre (SSRMC) training programme - a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

• A background in basic statistical theory and regression methods
• A working knowledge of statistical concepts up to the level of Linear Regression
• To use the Titan Teaching Room computers you must bring your password for the Desktop Services system. Please note, your password for the Desktop Services system is distinct from your Raven/department/email password. If you are uncertain about this you are advised to go to the University Computing Service Helpdesk before the first day of class or find out more on the UCS Newcomers page.
• You must have access to the associated Moodle course page (http://www.ssrmc.group.cam.ac.uk/ssrmc-modules/before-first-session)

Number of sessions: 2

• Introduction to Time Series
• Time Series Regression
• Smoothing Moving average
• Decomposition Methods

Presentations, demonstrations and practicals

• One online exercise [optional, dependent upon department]
• The SSRMC encourages all students to take the assessment

Bowerman, B.L. O'Connell, R. & Koehler, A (2004). Forecasting Time Series and Regression (4th ed). Duxbury Press

All students are expected to give feedback for each module they take...

At the end of each module, students will be sent a link to a very short evaluation form. They will also be able to find this link on the Moodle page for their course. The survey takes a few minutes to fill in, and can even be done on a mobile phone. Students that do not respond to the survey the first time, will receive regular automated reminders until the survey is completed.

Students will not be given certification or proof of attendance for any module for which they have not provided feedback.

• To gain maximum benefits from the course it is important that students do not see this course in isolation from the other MPhil courses or research training they are taking.
• Responsibility lies with each student to consider the potential for their own research using methods common in fields of the social sciences that may seem remote. Ideally this task will be facilitated by integration of the SSRMC with discipline-specific courses in their departments and through reading and discussion.

2 sessions of 4 hours (1 x lecture, 1 x lab)

8 hours - A morning lecture and an afternoon lab session
This is an intensive, one-day module