IBM SPSS - Intermediate: Missing Data Analysis

Course description

Most quantitative orientated research projects will face the problem of incomplete data. This workshop aims to provide an introduction to the missing data analysis. Issues related to: the types of ‘missingness’, consequences of missing data, ways of detecting it and methods of handling incomplete data, will be addressed in the course. Hands on components will introduce tools available in SPSS that support missing data analysis. 

This course is under great demand. If your circumstances change and you cannot attend, please cancel your enrolment as quickly as possible.

The details of the connection to the Web Conference will be emailed to enrolled participants a day before the course and again an hour before the event.

Type of course

Web conference


Pawel Skuza

Who should attend

Staff and Research Higher Degree Students

What you will learn

  • Brief theoretical introduction to the topic
  • Ways of preventing missing data by research design
  • The use of ‘missing data diagnostics tools’ available in SPSS
  • Methods of dealing with missing data

Prerequisites / assumed knowledge

Preferably participants should attend Introduction to SPSS and Introduction to Statistical Analysis (or have an understanding of concepts/skills covered in those two introductory courses) before enrolling in this workshop.


Upcoming events

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Waiting list

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