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Mon 21 Jan, Mon 28 Jan, ... Mon 11 Feb 2013
16:00 - 18:00

Venue: University Information Services, Titan Teaching Room 1, New Museums Site

Provided by: Social Sciences Research Methods Centre


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Module 04: Linear Regression (Series 2) *Taught using R software
BeginnersPrerequisitesNewUpdated

Mon 21 Jan, Mon 28 Jan, ... Mon 11 Feb 2013

Description

This module is part of the Social Science Research Methods Centre training 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.

Module 4 introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using R and how to access and solve possible problems with a regression model.

Target audience
  • MPhil and PhD students from participating departments taking the Social Science Research Methods Course as part of their research degree
Prerequisites
  • Students expected to have solid understanding of topics discussed in Modules 1-3.
  • Students need to have firm knowledge of covariance, correlation, and comparison of means.
  • Students also need to have working knowledge of using R (but class notes are provided).
Sessions

Number of sessions: 4

# Date Time Venue Trainer
1 Mon 21 Jan 2013   16:00 - 18:00 16:00 - 18:00 University Information Services, Titan Teaching Room 1, New Museums Site map N. Janz
2 Mon 28 Jan 2013   16:00 - 18:00 16:00 - 18:00 University Information Services, Titan Teaching Room 1, New Museums Site map N. Janz
3 Mon 4 Feb 2013   16:00 - 18:00 16:00 - 18:00 University Information Services, Titan Teaching Room 1, New Museums Site map N. Janz
4 Mon 11 Feb 2013   16:00 - 18:00 16:00 - 18:00 University Information Services, Titan Teaching Room 1, New Museums Site map N. Janz
Topics covered
  • Session 1: Review of concepts/introduction to bivariate regression
  • Session 2: Multiple linear regression
  • Session 3: Regression diagnostics I
  • Session 4: Regression diagnostics II - taking regression further.
Objectives
  • The objective is to learn the assumptions underlying regression models
  • To run regression analysis using R
  • To assess an solve possible problems with a regression model
Aims
  • To learn fundamental statistical techniques - regression analysis
Format

Presentations, demonstrations and practicals

Taught using

R on MCS

Assessment
  • One online assessment
Textbook(s)

Throughout all introductory statistics modules the main textbook is:

  • Field, Andy (2009), Discovering Statistics using SPSS. London:Sage
Notes
  • 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.
Duration

Four sessions of two hours.

Frequency

Once a week for four weeks.


Booking / availability