4.1 Read 125 reviews
Featured byUCL
Overview
UCL's Introduction to Dealing with Missing Data (Online) course provides guidance on how to deal with missing values and the best ways of analysing a dataset that is incomplete.
Key facts
- Missing data are very common in research studies, but ignoring these cases can lead to invalid and misleading conclusions being drawn.
Programme Structure
Courses include:
- Reasons for missing data
- Types of missing data
- Simple methods for analysing incomplete data
- More sophisticated methods of dealing with missing data (simple and multiple stochastic imputation, weighting methods)
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Campus Location
- London, United Kingdom
Disciplines
Data Science & Big Data View 40 other Short Courses in Data Science & Big Data in United KingdomWhat students do after studying
Join for free or log in to access our complete career info list.
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
A basic level of statistical literacy is required as a prerequisite.
It is desirable for the course participants to have basic knowledge of statistics, i.e. notion of statistical inference, p-values and Confidence intervals.
Those who have completed the five-day Introduction to Statistics and Research Methods course run frequently by the Centre for Applied Statistics Courses (CASC) team will be equipped.
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
-
International Applies to you
Applies to youNon-residents75 GBP / full≈ 75 GBP / full -
Domestic Applies to you
Applies to youCitizens or residents75 GBP / full≈ 75 GBP / full
Funding
Improve page content