Orthogonal Rotation: Get Info & Tips

In summary, orthogonal rotation is a statistical technique used in factor analysis to simplify the interpretation of complex data by rotating the axes of a multidimensional space. It is important because it can help identify underlying factors or patterns in data and reduce the number of variables needed to explain the data. There are several benefits to using orthogonal rotation, including easier data interpretation and identifying relationships and patterns. This technique works by minimizing the correlation between factors and some common types of orthogonal rotation include varimax, quartimax, equamax, and promax.
  • #1
Petrus
702
0
Hello MHB,
Do anyone know any good page that give you good describe when you rotate with orthogonal. I mean when you rotate base or vector in a orthogonal base ( hope this make sense) cause I did not understand from my book :(

Regards,
\(\displaystyle |\pi\rangle\)
 
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  • #2

FAQ: Orthogonal Rotation: Get Info & Tips

What is orthogonal rotation?

Orthogonal rotation is a statistical technique used in factor analysis to simplify the interpretation of complex data. It involves rotating the axes of a multidimensional space to produce a simpler and more meaningful structure for the data.

Why is orthogonal rotation important?

Orthogonal rotation is important because it can help researchers identify underlying factors or patterns in large sets of data. By simplifying the structure of the data, it can also make it easier to interpret and draw meaningful conclusions from the data.

What are the benefits of using orthogonal rotation?

One of the main benefits of using orthogonal rotation is that it can help to reduce the number of variables needed to explain a set of data. This can make the data easier to understand and analyze, and can also help to identify important relationships and patterns.

How does orthogonal rotation work?

Orthogonal rotation works by rotating the axes of a multidimensional space to produce a simpler and more meaningful structure for the data. This is typically done by minimizing the correlation between the factors, which can help to identify underlying patterns and relationships in the data.

What are some common types of orthogonal rotation?

Some common types of orthogonal rotation include varimax, quartimax, equamax, and promax. Each type of rotation has its own specific method for rotating the axes and has different advantages and disadvantages depending on the data being analyzed.

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