Visualization and Imputation of Missing Data
Learn to create numerous unique visualizations to better understand patterns of missing data in your data sample.
Affiliate disclosure: if you enroll through links on this page, the course provider may pay us a commission. This comes at no extra cost to you and does not influence how we describe courses.
What You'll Learn in This Course
Master key concepts and practical skills through structured learning modules. By completing this curriculum, you'll gain valuable expertise applicable to real-world scenarios.
Learning Outcome 1
Use visualizations created by R software to identify patterns of 'missingness' in data sets and to impute reasonable values to replace the missing data.
Learning Outcome 2
Recognize and identify the different patterns of missing data and the relative severity of their likely consequences.
Learning Outcome 3
Learn to use the VIM and VIMGUI R packages to create unique, novel and vibrant images which promote the understanding of patterns of both missing and imputed data in a set of data.
Learning Outcome 4
Learn the different historical approaches to impute reasonable values for missing data and their relative advantages and disadvantages.
Learning Outcome 5
Learn the characteristics of: (1) Hot-Deck; (2) K-Nearest Neighbor; (3) Regression-Based; and (4) Iterative, Model-Based, Stepwise Regression (IRMI) imputation techniques to "fill in" missing data and when and how to implement them with provided software.
Skills You'll Develop
This comprehensive Visualization and Imputation of Missing Data curriculum is designed to take you from foundational concepts to advanced implementation. Each module builds upon the previous, ensuring a structured learning path that maximizes knowledge retention and practical application.
Course Requirements & Target Audience
Understand what you need to succeed in this course and determine if it's the right fit for your learning goals
Prerequisites & Requirements
What you need before starting this Visualization and Imputation of Missing Data course:
- Students will need to install R software but ample instructions for doing so are provided.
Who This Course Is For
This course is perfect for:
- Motivated learners at any level
- Self-paced students
- Anyone interested in the subject
This course might not be suitable if:
- • You're looking for a quick tutorial rather than comprehensive learning
- • You prefer learning without structured curriculum
- • You need highly specialized or niche content
Course Information & Details
Everything you need to know about this online course, from duration to certification
Course Instructor
Geoffrey Hubona, Ph.D.
Expert instructor with industry experience
Course Language
English
All materials in English
Start Your Learning Journey Today
This online course offers comprehensive training with expert instruction, practical exercises, and a certificate of completion. Join thousands of students advancing their careers through quality online education.
Course Enrollment
Budget-Friendly Course
Typically around $49.99
Pricing may vary. Check the course provider for current promotions and exact pricing.
What's Included
- 5 hours on-demand video
- 4 downloadable resources
- Access on mobile and TV
- Certificate of Completion
- Full lifetime access
Affiliate disclosure: if you enroll through links on this page, the course provider may pay us a commission. This comes at no extra cost to you and does not influence how we describe courses.
- ✓Instant access after enrollment
- ✓Learn at your own pace
- ✓Direct enrollment with Udemy
Where this course fits
Wider context: the fields we cover, the glossary and certification exams, all written by us rather than pulled from a provider feed.