skip to navigation skip to content
Mon 21 Feb, Mon 28 Feb, ... Mon 14 Mar 2011
14:00 - 16:00

Venue: Phoenix Teaching Room

Provided by: Joint Schools' Social Sciences


Booking

Bookings cannot be made on this event (Event is in the past).


Other dates:


2012


2021



Register interest
Register your interest - if you would be interested in additional dates being scheduled.


Booking / availability

Module 10:Time Series Analysis
Prerequisites

Mon 21 Feb, Mon 28 Feb, ... Mon 14 Mar 2011

Description

This module is part of the Social Science Research Methods Course programme which is 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.

The module introduces time series techniques relevant to forecasting in social science research and computer implementation of the methods.

Target audience

Mphil Students from participating departments taking the Social Science Research Methods Course as part of their research degree

Prerequisites
  • Students need a background in basic statistical theory and working knowldge of SPSS
  • Students strongly recommended to complete Module 4 Linear Regression before attending this module.
Sessions

Number of sessions: 4

# Date Time Venue Trainer
1 Mon 21 Feb 2011   14:00 - 16:00 14:00 - 16:00 Phoenix Teaching Room Dr H.X. Bao
2 Mon 28 Feb 2011   14:00 - 16:00 14:00 - 16:00 Phoenix Teaching Room Dr H.X. Bao
3 Mon 7 Mar 2011   14:00 - 16:00 14:00 - 16:00 Phoenix Teaching Room Dr H.X. Bao
4 Mon 14 Mar 2011   14:00 - 16:00 14:00 - 16:00 Phoenix Teaching Room Dr H.X. Bao
Topics covered
  • Session 1: Introduction to Time Series
  • Session 2: Time Series Regression
  • Session 3: Smoothing
  • Session 4: Decomposition Methods
Objectives

The objective is to understand moving average; exponential smoothing and decomposition

Aims
  • To learn time series techniques relevant to forecasting in social science research and computer implementation of methods.
Format

Presentations, demonstrations and practicals

Assessement

Three exercises

Textbook(s)

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

Notes
  • To gain the 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
Duration

Four sessions of two hours

Frequency

Four times in Lent term

Themes

Booking / availability

Override user: