Title:
Perfect the Imperfect Data - How to Deal with Missing Data in Practice
Abstract:
No data would be perfect because of imperfect design or data collection process. Missing data is often inevitable in practice. In order to help researchers handle missing data properly, cause, consequence, analysis methods and prevention suggestions of missing data will be all introduced. In this workshop. Case studies in SPSS will be presented as well.
Outline
1. Types of Missing Data
2. Consequence of Missing Data
3. Analysis of Missing Data
4. Preventing Missing Data
Location
Pharmacy/Biology Building (PBB) 129
Date
11:00 AM – 12:00 PM, April 5, 2019
Registration: http://merlot.stat.uconn.edu/www/consulting/workshops/register.php
Live streaming is available at https://ait.uconn.edu/live-streaming/.
For more information, contact: Tracy Burke at tracy.burke@uconn.edu