Cluster Analysis- Theory & workout using SAS and R
What you'll learn
- Learn cluster analysis in crystal clear and simple way
- Learn hierarchical and non-hierarchical clustering
- Know theory, business apllication, sas program and interpretation of output
- R syntax for clustering
Requirements
- Basic understanding of statistics
- Basic knowledge of SAS
- Basic knowledge of R
Description
- About the course - Cluster analysis is one of the most popular techniques used in data mining for marketing needs. The idea behind cluster analysis is to find natural groups within data in such a way that each element in the group is as similar to each other as possible. At the same time, the groups are as dissimilar to other groups as possible.
- Course materials- The course contains video presentations (power point presentations with voice), pdf, excel work book and sas codes.
- Course duration- The course should take roughly 10 hours to understand and internalize the concepts.
- Course Structure (contents) The structure of the course is as follows.
Part 01 - cluster analysis theory and workout using SAS
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Motivation –
- Where one applies cluster analysis. Why one should learn cluster analysis?
- How it is different from objective segmentation (CHAID / CART )
Statistical foundation and practical application: Understand
- Different type of cluster analysis
- Cluster Analysis – high level view
- Hierarchical clustering –
- Agglomerative or Divisive technique
- Dendogram – What it is? What does it show?
- Scree plot - How to decide about number of clusters
- How to use SAS command to run hierarchical clustering
- When and why does on need to standardize the data?
- How to understand and interpret the output
- Non-hierarchical clustering (K means clustering).
- Why do we need k means approach
- How does it work?
- How does it iterate?
- How does it decide about combining old clusters?
- How to use SAS command to run hierarchical clustering
- When and why does on need to standardize the data?
- How to understand and interpret the output
Part 02
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Learn R syntax for hierarchical and non hierarchical clustering
Part 03
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Cluster analysis in data mining scenario
Part 04
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Assignment on cluster analysis
Who this course is for:
- statistics and analytics professionals / students
Instructor
![Gopal Prasad Malakar](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.3 Instructor Rating
- 10,102 Reviews
- 108,893 Students
- 17 Courses
I am a seasoned Analytics professional with 20+ years of professional experience. I have industry experience of impactful and actionable analytics, data science, decision strategy and enterprise wise data strategy.
I am a keen trainer, who believes that training is all about making users understand the concepts. If students remain confused after the training, the training is useless. I ensure that after my training, students (or partcipants) are crystal clear on how to use the learning in their business scenarios.
My expertise is in Credit Card Business, Scoring (econometrics based model development), score management, loss forecasting, business intelligence systems like tableau /SAS Visual Analytics, MS access based database application development, Enterprise wide big data framework and streaming analysis.
Please refer to my course for
- SAS / R program details (syntax and options)
- SAS / R output deep dive
- Practical usage in Industrial situation