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NVivo for Qualitative Data Analysis

6th December 2018 @ 8:00 am - 5:00 pm

The University of Manchester
Presenter Patty Dornan
Date 06/12/2018
Venue University of Manchester
Map View in Google Maps  (M13 9PL)
Contact CMI Short Courses
[email protected]
0161 2751980
Description This course introduces NVivo as a data management tool.

The structure of the training session will be a combination of formal presentation alongside practical application. Those attending the training session will have access to data sets for practical sessions and can also bring their own data to use in the practical parts of the session.  Among the techniques we teach are:  coding, adding attributes, queries, models, and charts.

The various uses of NVivo will be presented and discussed.  Included will be working in teams, adding in notes, importing files, and using NVivo for managing literature.  Examples of qualitative and mixed methods research will be presented to showcase how NVivo can be used to manage large amounts of various data.

Objectives

  • To explore basic, intermediate and advanced menu options in NVivo.
  • To produce queries, word clouds, and models that help with the analysis of qualitative data.
  • To analyse qualitative data in a transparent, reproducible way so that teams can work on the database.
Level Entry (no or almost no prior knowledge)
Cost £195 (£140 for those from educational, government and charitable institutions)
Website and registration
Region North West
Keywords Digital Social Research, Analysis of social media, Mixed Methods, Data Management , Data Quality and Data Management (other), Qualitative Data Handling and Data Analysis, NVivo
Related publications and presentations Digital Social Research
Analysis of social media
Mixed Methods
Data Management
Data Quality and Data Management (other)
Qualitative Data Handling and Data Analysis
NVivo

Details

Date:
6th December 2018
Time:
8:00 am - 5:00 pm
Event Category:
Website:
https://www.ncrm.ac.uk/training/show.php?article=8713
NINE DTP - a collaborative partnership funded by the ESRC