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Cathie Marsh Institute for Social Research (CMI)

Introduction to Data Analysis 1

Dates: 7 November 2019 and 23 April 2020
Time: 10am - 4.30pm
Instructor: Patricio Troncoso Ruiz and Jack Bailey 
Level: Introductory
Fee: £195 (£140 for those from educational, government and charitable institutions). 

CMI offers up to five subsidised places at a reduced rate of £60 per course day to research staff and students within Humanities at The University of Manchester. These places are awarded in order of application. 

Please note: this is not guaranteed and is considered on a case by case basis. Please contact us for more information.

Outline

Introduction to Data Analysis 1 is designed for those who would like to know more about the theory and practice of quantitative methods, but lack a background in statistics. Rather than burdensome mathematics, the course focuses on practical research skills. In particular, it emphasises hands-on practical learning and uses real-world data and cutting-edge software.

Objectives

This course covers the following topics:

  • Collecting data from surveys and other sources
  • Different types of data and how to analyse them
  • Describing and summarising data
  • Data management skills
  • Visualising data and findings

Prerequisites

None/Basic computer literacy.

Recommended reading

  • R for Data Science by Garrett Grolemund & Hadley Wickham

  • Discovering Statistics Using R by Andy Field, Jeremy Miles & Zoe Field

  • Social Research Methods by Alan Bryman

About the instructor

Jack Bailey is a doctoral researcher at the University of Manchester’s Department of Politics. His research focuses on how voters update their opinions in light of economic change and how this process affects their voting behaviour. Prior to starting his PhD, Jack completed the University’s MSc in Social Research Methods and Statistics. He also worked at Cardiff University and the London School of Economics and Political Science communicating research findings to the general public. This interest remains and motivates his approach to teaching statistics to non-specialist audiences.

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