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Guest Lecture by Mr. Uday Bhate, Topic:- “Advanced Statistics – Multidimensional Scaling”

Guest Lecture by Mr. Uday Bhate, Topic:- “Advanced Statistics – Multidimensional Scaling”

Date : February 05, 2020

A guest lecture was conducted by Mr. Uday Bhate about Multidimensional Scaling on February 05, 2020 at SIBM Hyderabad. Mr. Uday Bhate is also a Visiting Faculty for several statistics related subjects primarily focusing on SPSS software.

Mr. Uday Bhate addressing to SIBM, Students

Mr. Uday Bhate began the session by telling the students about what multidimensional scaling is and what it is used for. Multidimensional Scaling is a visual representation of distances or dissimilarities between sets of objects. The term scaling comes from psychometrics, where abstract concepts or objects are assigned numbers according to a rule. The “multidimensional” part is due to the fact that you aren’t limited to two dimensional graphs or data. Three-dimensional, four-dimensional and higher plots are possible.

Multidimensional Scaling is useful when we are only given a set of differences, and the goal is to create a map or connections that will also tell you what the original distances where and where they were located. 2D graphs are easy to formulate and interpret while 3D graphs are harder to interpret.

Mr. Uday Bhate then told the students about the difference between Multidimensional scaling and Factor Analysis. Both Multidimensional scaling and Factor Analysis uncover hidden patterns or relationships in data. Both techniques require a matrix of measures of associations. However, while Factor Analysis requires metric data while, Multidimensional scaling can handle both metric and non-metric data. Multidimensional scaling is more useful than Factor Analysis if you are able to create a 2D map, as you’all will be able to visually confirm your findings.

The session was interesting and the students learnt a lot about Multidimensional Scaling, the process of performing Multidimensional Scaling using SPSS, the application of Multidimensional Scaling and its comparison with Factor analysis. It was a very useful data analysis tool that students can use in the future.

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